Top SAP Data Warehouse Cloud Alternatives

BigQuery serves as a serverless, multicloud data warehouse that simplifies the handling of diverse data types, allowing businesses to quickly extract significant insights. As an integral part of Google’s data cloud, it facilitates seamless data integration, cost-effective and secure scaling of analytics capabilities, and features built-in business intelligence for disseminating comprehensive data insights. With an easy-to-use SQL interface, it also supports the training and deployment of machine learning models, promoting data-driven decision-making throughout organizations. Its strong performance capabilities ensure that enterprises can manage escalating data volumes with ease, adapting to the demands of expanding businesses. Furthermore, Gemini within BigQuery introduces AI-driven tools that bolster collaboration and enhance productivity, offering features like code recommendations, visual data preparation, and smart suggestions designed to boost efficiency and reduce expenses. The platform provides a unified environment that includes SQL, a notebook, and a natural language-based canvas interface, making it accessible to data professionals across various skill sets. This integrated workspace not only streamlines the entire analytics process but also empowers teams to accelerate their workflows and improve overall effectiveness. Consequently, organizations can leverage these advanced tools to stay competitive in an ever-evolving data landscape.

Grow is an all-in-one, no-code business intelligence (BI) platform designed to enable every member of your organization to make decisions based on data. Organizations can seamlessly connect to their data and extract valuable insights by integrating ETL processes, data warehousing, and visualization tools within a single platform. With our unlimited-user license model, all users can obtain the information they need without waiting for an analyst's assistance, empowering everyone to make informed decisions in real time and drive their growth forward. Additionally, Grow offers: - Unlimited user access - Over 100 integrations - No SQL knowledge needed (though it is an option) - Support from BI consultants - Simplified ETL processes - Interactive dashboards that adapt to your needs

Improvado is an ETL platform designed to automate data pipelines for marketing teams, enabling users without technical expertise to harness the power of data. This tool empowers marketers to make strategic, data-informed decisions by providing a holistic approach to integrating marketing data throughout the organization. It efficiently extracts information from various marketing data sources, standardizes it, and loads it directly into user-friendly marketing dashboards. With more than 200 pre-built connectors available, Improvado ensures a wide array of integrations, and the dedicated team is also willing to develop new connectors upon client request. By utilizing Improvado, marketers can centralize their data, enhance their understanding of performance across different channels, evaluate attribution models, and access precise Return on Marketing Investment (ROMI) metrics. Well-known companies such as Asus, BayCare, and Monster Energy have adopted Improvado to strengthen their marketing efforts. This platform not only simplifies data management but also fosters a culture of data-driven decision-making within organizations.

SAP BW/4HANA is a comprehensive data warehouse solution that harnesses the power of SAP HANA technology. As a key component of SAP’s Business Technology Platform for on-premise use, it enables the aggregation of enterprise data, creating a coherent and mutually accepted perspective across the organization. This system acts as a singular source for immediate insights, streamlining processes and encouraging innovation. By utilizing the advanced features of SAP HANA, this robust data warehouse allows organizations to fully realize the potential of their data, regardless of its origin, whether from SAP applications, external systems, or various data types, including unstructured, geospatial, or Hadoop-based content. Companies can revamp their data management strategies to boost efficiency and responsiveness, thus facilitating the implementation of real-time insights on a large scale, whether in an on-premise setting or via cloud solutions. Moreover, it promotes the digital transformation of various business sectors and integrates effortlessly with SAP’s digital business platform offerings. This holistic approach not only enhances decision-making but also drives significant improvements in operational effectiveness, positioning businesses for success in a data-driven landscape. Ultimately, organizations can harness the power of their data to innovate and thrive in today’s competitive environment.

Amazon Redshift stands out as the favored option for cloud data warehousing among a wide spectrum of clients, outpacing its rivals. It caters to analytical needs for a variety of enterprises, ranging from established Fortune 500 companies to burgeoning startups, helping them grow into multi-billion dollar entities, as exemplified by Lyft. The platform is particularly adept at facilitating the extraction of meaningful insights from vast datasets. Users can effortlessly perform queries on large amounts of both structured and semi-structured data throughout their data warehouses, operational databases, and data lakes, utilizing standard SQL for their queries. Moreover, Redshift enables the convenient storage of query results back to an S3 data lake in open formats like Apache Parquet, allowing for further exploration with other analysis tools such as Amazon EMR, Amazon Athena, and Amazon SageMaker. Acknowledged as the fastest cloud data warehouse in the world, Redshift consistently improves its speed and performance annually. For high-demand workloads, the newest RA3 instances can provide performance levels that are up to three times superior to any other cloud data warehouse on the market today. This impressive capability establishes Redshift as an essential tool for organizations looking to optimize their data processing and analytical strategies, driving them toward greater operational efficiency and insight generation. As more businesses recognize these advantages, Redshift’s user base continues to expand rapidly.

The Oracle Autonomous Data Warehouse is a cloud-native solution crafted to alleviate the complex issues related to managing a data warehouse, such as cloud operations, ensuring data security, and developing data-driven applications. This innovative service automates key tasks including provisioning, configuration, security protocols, performance tuning, scaling, and data backup, thereby optimizing the overall user experience. It also provides self-service capabilities for data loading, transformation, and business modeling, along with automated insights and integrated converged database features that simplify querying across various data formats and support machine learning tasks. Accessible via the Oracle public cloud or Oracle Cloud@Customer deployed within client facilities, it grants organizations the flexibility they need. According to industry experts at DSC, Oracle Autonomous Data Warehouse presents significant advantages, positioning it as a top choice among many global corporations. Additionally, a variety of applications and tools seamlessly integrate with the Autonomous Data Warehouse, further boosting its functionality and user effectiveness, making it an invaluable asset for businesses looking to harness their data effectively.

SAP Datasphere acts as a unified data experience platform within the SAP Business Data Cloud, designed to provide seamless and scalable access to vital business information. It effectively merges data from both SAP and non-SAP sources, promoting a cohesive data environment that enhances the speed and accuracy of decision-making. The platform includes features like data federation, cataloging, semantic modeling, and real-time data integration, which help organizations sustain consistent and contextualized data in both hybrid and cloud environments. Additionally, SAP Datasphere simplifies data management by preserving business context and logic, thereby delivering a comprehensive view of data that fosters innovation and improves business workflows. This integration not only enables businesses to utilize their data more efficiently but also positions them to thrive in a competitive market. As a result, organizations can make informed strategic choices that drive growth and success.

The Agile Data Engine functions as a powerful DataOps platform designed to enhance the entire lifecycle of creating, launching, and overseeing cloud-oriented data warehouses. This cutting-edge solution merges various elements like data modeling, transformation, continuous deployment, workflow orchestration, monitoring, and API connectivity into a single SaaS package. By utilizing a metadata-driven approach, it automates the creation of SQL code and the implementation of data loading workflows, thereby significantly increasing efficiency and adaptability in data operations. The platform supports multiple cloud database options, including Snowflake, Databricks SQL, Amazon Redshift, Microsoft Fabric (Warehouse), Azure Synapse SQL, Azure SQL Database, and Google BigQuery, offering users considerable flexibility across various cloud ecosystems. Furthermore, its modular design and pre-configured CI/CD pipelines empower data teams to integrate effortlessly and uphold continuous delivery, enabling rapid responses to changing business requirements. In addition, Agile Data Engine provides critical insights and performance metrics, giving users the essential resources to oversee and refine their data platforms. This comprehensive functionality not only aids organizations in optimizing their data operations but also helps them sustain a competitive advantage in an ever-evolving data-driven environment. As businesses navigate this landscape, the Agile Data Engine stands out as an essential tool for success.

Panoply simplifies the process of storing, synchronizing, and accessing all your business data in the cloud. Thanks to its seamless integrations with leading CRMs and file systems, creating a unified repository for your information is now more straightforward than ever. The platform is designed for rapid deployment and does not necessitate continuous upkeep, making it a hassle-free solution. Additionally, Panoply provides exceptional customer support and offers flexible plans tailored to various requirements, ensuring that every business can find a suitable option.

AnalyticDB for MySQL stands out as a robust data warehousing solution, engineered to offer security, dependability, and ease of use. It allows for the effortless production of online statistical reports, multidimensional analysis structures, and real-time data warehousing. Thanks to its distributed computing design, AnalyticDB for MySQL takes advantage of the cloud's scalable nature to manage enormous data volumes, effortlessly accommodating tens of billions of records in real-time. The service organizes data through relational models and supports versatile computation and analysis via SQL. Additionally, it makes database management more straightforward, giving users the flexibility to scale nodes and modify instance sizes as necessary. With a comprehensive suite of visualization and ETL tools, AnalyticDB for MySQL greatly enhances the efficiency of enterprise data processing. Users can perform instantaneous multidimensional analysis, sifting through massive datasets in mere milliseconds, thus delivering critical insights without delay. Furthermore, its extensive features enable organizations to effectively meet their data needs while remaining agile in the face of evolving requirements, ensuring long-term business success. Overall, this solution is pivotal for any business aiming to leverage data for strategic decision-making.

Presenting a revolutionary cloud data lakehouse that is fully managed and designed to ingest data from all your sources within minutes, while efficiently supporting every query engine on a large scale, all at a notably lower cost. This platform allows for the ingestion of data from both databases and event streams at a terabyte scale in near real-time, providing the convenience of completely managed pipelines. Moreover, it enables you to execute queries with any engine, catering to various requirements including business intelligence, real-time analytics, and AI/ML applications. By utilizing this solution, you can achieve over a 50% reduction in costs compared to conventional cloud data warehouses and ETL tools, thanks to a clear usage-based pricing model. The deployment process is rapid, taking mere minutes, and is free from engineering burdens due to its fully managed and highly optimized cloud service. You can consolidate your data into a unified source of truth, which eliminates the need for data duplication across multiple warehouses and lakes. Choose the ideal table format for each task and enjoy seamless interoperability among Apache Hudi, Apache Iceberg, and Delta Lake. Additionally, you can quickly establish managed pipelines for change data capture (CDC) and streaming ingestion, which ensures that your data architecture remains agile and efficient. This cutting-edge approach not only simplifies your data workflows but also significantly improves decision-making processes throughout your organization, ultimately leading to more informed strategies and enhanced performance. As a result, the platform empowers organizations to harness their data effectively and proactively adapt to evolving business landscapes.

Unlock the potential for effortless sales growth by leveraging automated data pipelines that seamlessly integrate with data lakes or cloud storage solutions, all without requiring any coding expertise. This versatile platform aligns with industry standards, allowing for the unification of sales and marketing data to produce automated insights that drive smarter business expansion. Say goodbye to the burdens and expenses linked to tedious manual data downloads, as you'll maintain a transparent view of your costs, only paying for the services you actually utilize. Equip your tools with quick access to analytics-ready data, ensuring your operations run smoothly. Our certified developers emphasize security by exclusively utilizing official APIs, which guarantees reliable connections. You can swiftly set up data pipelines from popular platforms, giving you access to pre-built, pre-transformed pipelines that unlock essential data from sources like Amazon Vendor Central, Instagram Stories, Facebook, and Google Ads. The processes for data ingestion and transformation are designed to be code-free, enabling teams to quickly and cost-effectively tap into their data's full capabilities. Your data is consistently protected and securely stored in a trusted, customer-controlled destination, such as Databricks or Amazon Redshift, providing you with peace of mind while handling your data assets. This efficient methodology not only conserves time but also significantly boosts overall operational effectiveness, allowing your business to focus on growth and innovation. Ultimately, this approach transforms the way you manage and analyze data, paving the way for a more data-driven future.

Blendo emerges as the leading solution for ETL and ELT data integration, transforming how you connect various data sources to databases. With an array of natively designed connection options, Blendo simplifies the extract, load, transform (ETL) process, ensuring a user-friendly experience. This powerful tool enables you to automate your data management and transformation tasks, allowing you to uncover business intelligence insights much more rapidly. The hurdles associated with data analysis are no longer limited to warehousing, management, or integration challenges. Thanks to Blendo, you can seamlessly automate and synchronize data from any SaaS application right into your data warehouse. By using pre-built connectors, establishing a link to any data source is as easy as logging in, which means your data can start syncing in no time. Wave goodbye to the complexities of creating integrations, exporting data, or coding scripts. By saving crucial hours, you gain the opportunity to delve deeper into your business operations. Accelerate your path to meaningful insights with Blendo's dependable data, which is complemented by analytics-ready tables and schemas tailored for effortless analysis with any BI software, thus significantly enhancing your overall data strategy. Furthermore, Blendo's intuitive interface ensures that even users with minimal technical expertise can harness its full potential, making it an indispensable asset for teams aiming for data-driven decision-making.

bi(OS)® provides an unparalleled speed to insight for developers engaged in crafting data applications in a unified manner. Utilizing bi(OS)®, the entire development cycle of data applications can be accomplished in mere hours to a few days. This all-encompassing approach includes the seamless integration of varied data sources, the extraction of real-time insights, and the effortless deployment into production settings. Collaborating with enterprise data teams across multiple industries allows you to evolve into the data champion your organization requires. Despite the combination of Open Source, Cloud, and SaaS, the true potential for achieving authentic data-driven outcomes remains largely unrealized. Many enterprises have concentrated their resources on data movement and integration, a tactic that proves to be ultimately unsustainable. A new outlook on data management is critically needed, one that addresses the specific challenges faced by enterprises. bi(OS)® is conceived by reexamining essential principles in enterprise data management, encompassing everything from data ingestion to insight development. It effectively serves the needs of API, AI, and BI developers in a unified manner, facilitating data-driven results within a matter of days. As engineers work together efficiently, a synergistic relationship develops among IT teams, tools, and processes, which fosters a sustainable competitive edge for the organization. This innovative approach not only streamlines workflows but also empowers teams to harness the full potential of their data assets.

VeloDB, powered by Apache Doris, is an innovative data warehouse tailored for swift analytics on extensive real-time data streams. It incorporates both push-based micro-batch and pull-based streaming data ingestion processes that occur in just seconds, along with a storage engine that supports real-time upserts, appends, and pre-aggregations, resulting in outstanding performance for serving real-time data and enabling dynamic interactive ad-hoc queries. VeloDB is versatile, handling not only structured data but also semi-structured formats, and it offers capabilities for both real-time analytics and batch processing, catering to diverse data needs. Additionally, it serves as a federated query engine, facilitating easy access to external data lakes and databases while integrating seamlessly with internal data sources. Designed with distribution in mind, the system guarantees linear scalability, allowing users to deploy it either on-premises or as a cloud service, which ensures flexible resource allocation according to workload requirements, whether through the separation or integration of storage and computation components. By capitalizing on the benefits of the open-source Apache Doris, VeloDB is compatible with the MySQL protocol and various functions, simplifying integration with a broad array of data tools and promoting flexibility and compatibility across a multitude of environments. This adaptability makes VeloDB an excellent choice for organizations looking to enhance their data analytics capabilities without compromising on performance or scalability.

Enterprise Enabler consolidates diverse information from multiple sources and fragmented data sets into a single, cohesive platform; this encompasses data stored in the cloud, scattered across standalone databases, kept on various instruments, residing in Big Data repositories, or found within numerous spreadsheets and documents. By facilitating seamless integration of all your data, it equips you to make prompt and informed business decisions. The system constructs logical representations of data from its original sources, allowing you to effectively reuse, configure, test, deploy, and monitor everything within one unified environment. This capability enables you to analyze your business data as events progress, which aids in optimizing asset utilization, lowering costs, and refining your business processes. Notably, our deployment timeline is generally 50-90% faster, ensuring that your data sources are interconnected and functioning in a remarkably short period, thus supporting real-time decision-making based on the latest available information. With this innovative solution, organizations can boost collaboration and efficiency, resulting in enhanced overall performance and a competitive edge in the marketplace. Additionally, this strategic integration fosters a culture of data-driven insights, empowering teams to innovate and adapt swiftly to market changes.

Datapine's business intelligence and dashboard software enables users to swiftly transform their data into actionable insights, facilitating data-driven decision-making. With an intuitive drag-and-drop interface, both managers and data scientists can effectively visualize and analyze intricate data sets. Users are empowered to pose critical business questions and obtain immediate responses, enhancing their analytical capabilities. The platform boasts a rich array of advanced analytics features, such as predictive analytics and interactive dashboards, which support the development of KPI-focused business dashboards. Additionally, it offers numerous data connectors compatible with various common data sources, including databases, flat files, social media analytics, CRM, and ERP systems. The extensive collection of pre-made dashboard templates tailored for diverse business functions—such as marketing, sales management, and HR—and various industries, including retail, logistics, healthcare, and market research, further supports users. Platforms like Google Analytics, Facebook, Twitter, and Zendesk also contribute to a seamless onboarding experience for new users, ensuring they can leverage the software's capabilities from the outset.

IBM® Db2® Warehouse offers a preconfigured, client-managed data warehouse solution that operates seamlessly in private clouds, virtual private clouds, and various containerized settings. Designed to be an ideal hybrid cloud solution, it empowers users to maintain control over their data while enjoying the advantages of cloud flexibility. The platform incorporates integrated machine learning, automatic scaling, built-in analytics, and supports both SMP and MPP processing capabilities, allowing organizations to implement AI solutions more rapidly and easily. You can establish a pre-configured data warehouse within minutes on your preferred supported infrastructure, with elastic scaling that supports smooth updates and upgrades. By utilizing in-database analytics right where the data resides, companies can enhance their AI capabilities, resulting in faster and more efficient operations. Additionally, the ability to create your application once means you can shift workloads to the most appropriate environment—whether that's a public cloud, private cloud, or on-premises—while making minimal or no changes. This adaptability is crucial for businesses aiming to optimize their data strategies across a variety of deployment choices, ensuring they remain competitive in an ever-evolving market landscape. Furthermore, the user-friendly setup process and robust features make it an appealing option for organizations looking to harness the power of their data effectively.

Focus on crafting meaningful and influential reports and analytics instead of getting overwhelmed by the intricacies of data warehouse coding. It's essential to prevent your data warehouse from devolving into a disorganized collection of numerous challenging pipelines, notebooks, stored procedures, tables, and views. Dimodelo DW Studio significantly reduces the effort required for the design, construction, deployment, and management of a data warehouse. It supports the creation and implementation of a data warehouse tailored for Azure Synapse Analytics. By establishing a best practice architecture that integrates Azure Data Lake, Polybase, and Azure Synapse Analytics, Dimodelo Data Warehouse Studio guarantees the provision of a high-performing and modern cloud data warehouse. Additionally, the use of parallel bulk loads and in-memory tables further enhances the efficiency of Dimodelo Data Warehouse Studio, allowing teams to prioritize extracting valuable insights over handling maintenance tasks. This shift not only streamlines operations but also empowers organizations to make data-driven decisions with greater agility.

DataLakeHouse.io's Data Sync feature enables users to effortlessly replicate and synchronize data from various operational systems—whether they are on-premises or cloud-based SaaS—into their preferred destinations, mainly focusing on Cloud Data Warehouses. Designed for marketing teams and applicable to data teams across organizations of all sizes, DLH.io facilitates the creation of unified data repositories, which can include dimensional warehouses, data vaults 2.0, and machine learning applications. The tool supports a wide range of use cases, offering both technical and functional examples such as ELT and ETL processes, Data Warehouses, data pipelines, analytics, AI, and machine learning, along with applications in marketing, sales, retail, fintech, restaurants, manufacturing, and the public sector, among others. With a mission to streamline data orchestration for all organizations, particularly those aiming to adopt or enhance their data-driven strategies, DataLakeHouse.io, also known as DLH.io, empowers hundreds of companies to effectively manage their cloud data warehousing solutions while adapting to evolving business needs. This commitment to versatility and integration makes it an invaluable asset in the modern data landscape.

The Unified Analytics Warehouse stands out as an exceptional resource for accessing high-performance analytics and machine learning on a large scale. Analysts in the tech research field are identifying emerging leaders who aim to revolutionize big data analytics. Vertica enhances the capabilities of data-centric organizations, enabling them to maximize their analytics strategies. It provides sophisticated features such as advanced time-series analysis, geospatial functionality, machine learning tools, and seamless data lake integration, alongside user-definable extensions and a cloud-optimized architecture. The Under the Hood webcast series from Vertica allows viewers to explore the platform's features in depth, with insights provided by Vertica engineers, technical experts, and others, highlighting its position as the most scalable advanced analytical database available. By supporting data-driven innovators globally, Vertica plays a crucial role in their quest for transformative changes in industries and businesses alike. This commitment to innovation ensures that organizations can adapt and thrive in an ever-evolving market landscape.

Bring together all your data into a unified platform that boasts over 100 integrated API data connectors, enabling seamless access for your entire team. With simple point-and-click methods, you can easily transform your data without any hassle. Build robust data pipelines using built-in features for data manipulation and automated scheduling, which drastically cuts down the time required for manual data handling. Utilize Workflow to enhance automation across databases, business intelligence tools, and a variety of applications. In addition, a wide range of no-code tools for data cleaning and transformation eliminates the need for intricate coding or formulas. Keep in mind that data's true potential is realized when valuable insights are derived from it. Upgrade your database into a formidable analytical engine, complete with native cloud-based BI capabilities. As all data projects on Acho can be analyzed and visualized directly on our Visual Panel without needing extra connectors, insights are delivered rapidly while maintaining an accessible user experience. This comprehensive strategy not only facilitates quick and informed decision-making for teams but also fosters a collaborative environment where data-driven strategies can thrive.

Teradata has introduced VantageCloud, a comprehensive cloud analytics platform designed to accelerate innovation through data utilization. By integrating artificial intelligence, machine learning, and real-time data processing, VantageCloud enables businesses to transform raw data into actionable insights. The platform supports a wide range of applications, including advanced analytics, business intelligence, and cloud migration, while facilitating seamless deployment across public, hybrid, or on-premise environments. With Teradata’s robust analytical tools, organizations can fully leverage their data, improving operational efficiency and uncovering new growth opportunities across various industries. This versatility positions VantageCloud as an essential resource for businesses aiming to excel in an increasingly data-centric world. As companies continue to navigate the complexities of their respective markets, the dynamic capabilities of VantageCloud will play a crucial role in their success.

With the combination of specialized enterprise partnership expertise and a user-friendly, scalable data management suite, you can regain command over your data, access it globally, maintain security and compliance, and harness its potential for business growth. Why Choose Sesame Software? Relational Junction facilitates the automatic building, population, and incremental refreshing of your data. Improve Data Quality - Transform data from diverse sources into a uniform format, resulting in enhanced accuracy that underpins sound decision-making. Extract Insights - By automating the aggregation of information into a centralized location, you can leverage your internal BI tools to create valuable reports, helping you sidestep expensive errors. Consistent Pricing - Eliminate unpredictable costs with fixed yearly pricing and long-term discounts, regardless of your data volume. With these advantages, your organization can unlock new opportunities and streamline operations.

AtScale optimizes and simplifies business intelligence, resulting in faster insights, enhanced decision-making, and increased returns on cloud analytics investments. By alleviating the burden of tedious data engineering tasks like data curation and delivery for analysis, AtScale enables teams to concentrate on crucial strategic initiatives. The centralization of business definitions guarantees consistency in KPI reporting across various business intelligence platforms. This innovative solution not only accelerates the insight-gathering process but also manages cloud computing costs more efficiently. You can leverage existing data security measures for analytics, irrespective of where the data resides. With AtScale’s Insights workbooks and models, users can perform multidimensional Cloud OLAP analyses on data from multiple sources without needing to prepare or engineer the data beforehand. Our user-friendly dimensions and measures are crafted to expedite insight generation that directly influences business strategies, allowing teams to make well-informed decisions swiftly. Ultimately, AtScale equips organizations to unlock the full potential of their data while reducing the complexities typically associated with conventional analytics processes. Furthermore, this approach fosters a more agile environment where data-driven insights can swiftly translate into actionable strategies, further enhancing overall business performance.

Discover a robust enterprise architecture and a cloud-based data platform powered by Snowflake® that facilitates secure data storage and management in the cloud. Featuring an integrated ETL process alongside an easy-to-use drag-and-drop visual workflow designer, you can seamlessly connect, cleanse, and transform data from more than 250 sources. Leverage state-of-the-art Search and AI technologies to swiftly produce insights and actionable analytics derived from your data in mere seconds. Take advantage of our sophisticated AI/ML environments to build, refine, and deploy predictive analytics and forecasting models with ease. Elevate your data capabilities even further with our all-encompassing AI/ML frameworks that empower you to design, train, and implement AI models via the PurpleCube Data Science module. Furthermore, create captivating BI visualizations using PurpleCube Analytics, delve into your data through natural language queries, and gain from AI-enhanced insights and intelligent recommendations that uncover answers to inquiries you may not have anticipated. This comprehensive strategy ensures that you are thoroughly prepared to make informed, data-driven decisions with both confidence and clarity, setting your organization on a path toward success. As you engage with this platform, you'll find that the possibilities for innovation and growth are virtually limitless.

The LoadSpring Cloud Platform emerges as an all-encompassing and highly adaptable solution for overseeing your projects, applications, and information seamlessly. It is essential to finally put your cloud maturity strategies and digital transformation efforts at the forefront. Our team of expert Cloud Sherpas guarantees a smooth journey without the usual pressures, allowing you to concentrate on what really counts. By employing the integrated LoadSpringInsight tool, you can enhance your profit margins with cutting-edge cloud business intelligence capabilities. You can choose to use our standard KPI tools or customize your data for improved decision-making processes. We are committed to driving innovation and optimizing your return on investment by streamlining software adoption and better managing licenses. Furthermore, we improve IT efficiency and expedite critical business assessments. Leverage succinct business intelligence reports to meet your KPI objectives, all backed by our robust data lake solutions. LoadSpringInsight is indeed the vital business analytics tool that every organization should have to flourish and prosper, as it is crafted to help businesses navigate intricate data environments with ease. As the digital landscape continues to evolve, embracing such tools becomes increasingly crucial for sustained growth and competitiveness.

Dapps utilizing Space and Time enable efficient blockchain interoperability by merging SQL and machine learning for data related to Gaming and DeFi, thus serving any decentralized applications that demand dependable tamperproofing, robust blockchain security, or enterprise-grade scalability. By fusing blockchain data with an advanced database, a connection is established between off-chain storage and on-chain analytics. This methodology fosters easier multi-chain integration, facilitates data indexing, and supports anchoring, allowing for the seamless combination of on-chain and off-chain information. Furthermore, it fortifies data security through well-established and reliable mechanisms. Users can choose their source data by linking to our indexed real-time blockchain information from numerous prominent chains, alongside integrating off-chain data they have accumulated. In addition, you can securely transmit tamperproof query results to smart contracts in a trustless setting or directly publish these results on-chain, backed by our pioneering cryptographic guarantees known as Proof of SQL. This innovative technology not only simplifies data management but also safeguards the integrity of the data throughout the entire process. Consequently, this enhances user confidence in using these decentralized applications, ensuring that data remains both accessible and secure.

We simplify and enhance the efficiency of Business Intelligence (BI) and Big Data analytics. Our aim is to equip business users and BI specialists, as well as busy professionals, to work independently when tackling data-centric challenges. Querona serves as a solution for anyone who has experienced the frustration of insufficient data, slow report generation, or long wait times for BI assistance. With an integrated Big Data engine capable of managing ever-growing data volumes, Querona allows for the storage and pre-calculation of repeatable queries. The platform also intelligently suggests query optimizations, facilitating easier enhancements. By providing self-service capabilities, Querona empowers data scientists and business analysts to swiftly create and prototype data models, incorporate new data sources, fine-tune queries, and explore raw data. This advancement means reduced reliance on IT teams. Additionally, users can access real-time data from any storage location, and Querona has the ability to cache data when databases are too busy for live queries, ensuring seamless access to critical information at all times. Ultimately, Querona transforms data processing into a more agile and user-friendly experience.

BigLake functions as an integrated storage solution that unifies data lakes and warehouses, enabling BigQuery and open-source tools such as Spark to work with data while upholding stringent access controls. This powerful engine enhances query performance in multi-cloud settings and is compatible with open formats like Apache Iceberg. By maintaining a single version of data with uniform attributes across both data lakes and warehouses, BigLake guarantees meticulous access management and governance across various distributed data sources. It effortlessly integrates with a range of open-source analytics tools and supports open data formats, thus delivering analytical capabilities regardless of where or how the data is stored. Users can choose the analytics tools that best fit their needs, whether they are open-source options or cloud-native solutions, all while leveraging a unified data repository. Furthermore, BigLake allows for precise access control across multiple open-source engines, including Apache Spark, Presto, and Trino, as well as in various formats like Parquet. It significantly improves query performance on data lakes utilizing BigQuery and works in tandem with Dataplex, promoting scalable management and structured data organization. This holistic strategy not only empowers organizations to fully utilize their data resources but also streamlines their analytics workflows, leading to enhanced insights and decision-making capabilities. Ultimately, BigLake represents a significant advancement in data management solutions, allowing businesses to navigate their data landscape with greater agility and effectiveness.

GeoSpock transforms the landscape of data integration in a connected universe with its advanced GeoSpock DB, a state-of-the-art space-time analytics database. This cloud-based platform is crafted for optimal querying of real-world data scenarios, enabling the synergy of various Internet of Things (IoT) data sources to unlock their full potential while simplifying complexity and cutting costs. With the capabilities of GeoSpock DB, users gain from not only efficient data storage but also seamless integration and rapid programmatic access, all while being able to execute ANSI SQL queries and connect to analytics platforms via JDBC/ODBC connectors. Analysts can perform assessments and share insights utilizing familiar tools, maintaining compatibility with well-known business intelligence solutions such as Tableau™, Amazon QuickSight™, and Microsoft Power BI™, alongside support for data science and machine learning environments like Python Notebooks and Apache Spark. Additionally, the database allows for smooth integration with internal systems and web services, ensuring it works harmoniously with open-source and visualization libraries, including Kepler and Cesium.js, which broadens its applicability across different fields. This holistic approach not only enhances the ease of data management but also empowers organizations to make informed, data-driven decisions with confidence and agility. Ultimately, GeoSpock DB serves as a vital asset in optimizing operational efficiency and strategic planning.

biGENIUS streamlines every aspect of analytic data management solutions, such as data lakes, data warehouses, and data marts, enabling you to transform your data into actionable business insights efficiently and economically. By employing these data analytics solutions, you can conserve valuable time, reduce effort, and lower costs. The platform facilitates the seamless incorporation of fresh ideas and data into your analytic frameworks. Utilizing a metadata-driven strategy enables you to leverage the latest technological advancements effectively. As digitalization progresses, traditional data warehouses and business intelligence systems must evolve to manage the growing volume of data effectively. Therefore, effective analytical data management has become crucial for contemporary business decision-making. This approach must incorporate new data sources, adapt to emerging technologies, and provide efficient solutions at an unprecedented speed, ideally while utilizing minimal resources. In this rapidly changing landscape, the ability to swiftly adjust to new requirements will determine the success of businesses.

IBM's industry data model acts as a detailed framework that integrates common elements consistent with best practices and regulatory requirements, designed to cater to the complex data and analytical needs of different fields. By adopting this model, businesses can efficiently manage their data warehouses and lakes, facilitating the extraction of deeper insights that enhance their decision-making capabilities. These models include blueprints for data warehouses, uniform business language, and business intelligence templates, all structured within a set framework that accelerates the analytics process for targeted industries. This approach allows for quicker analysis and the design of functional requirements by utilizing industry-specific informational infrastructures. Furthermore, organizations can create and refine data warehouses with a unified architecture that can adapt to changing demands, significantly reducing risks while improving data delivery to applications across the organization, which is essential for fostering transformation. It is also vital to establish enterprise-wide key performance indicators (KPIs) while catering to compliance, reporting, and analytical requisites. Moreover, implementing specialized vocabularies and templates for regulatory reporting is crucial for effectively managing and overseeing data assets, ensuring rigorous accountability and governance. This comprehensive strategy not only enhances operational efficiency but also equips organizations to react swiftly and effectively to the ever-evolving challenges within their industry environments. Ultimately, the integration of such a model fosters a culture of continuous improvement and responsiveness that can significantly benefit organizations in the long run.

IBM Db2 represents a comprehensive array of data management solutions, with a strong emphasis on the Db2 relational database. These solutions incorporate AI-driven features aimed at facilitating the management of both structured and unstructured data within a variety of on-premises and multicloud environments. By making data more accessible, the Db2 suite enables companies to fully harness the benefits of AI technology. Most of the Db2 components are seamlessly integrated into the IBM Cloud Pak® for Data platform, offered either as supplementary features or as inherent data source services, which guarantees that nearly all data is available across hybrid or multicloud infrastructures to support AI-centric applications. Users can easily consolidate their transactional data repositories and quickly gain insights through intelligent, universal querying across multiple data sources. The multimodel capabilities contribute to cost reduction by eliminating the need for data replication and migration. Furthermore, Db2 provides remarkable flexibility, allowing for deployment across any cloud service provider, thus enhancing operational agility and responsiveness. This range of deployment options ensures that organizations can modify their data management approaches to align with their evolving requirements, ultimately fostering innovation and adaptability in their operations. This adaptability is crucial for maintaining a competitive edge in today’s rapidly changing business landscape.

IBM's dashDB Local, the newest component of the dashDB suite, strengthens the company's hybrid data warehouse initiative by providing businesses with a flexible architecture that minimizes analytics costs amid the fast-changing realms of big data and cloud services. This is made possible through an integrated analytics engine that accommodates multiple deployment options in both private and public cloud settings, facilitating smooth transitions and optimization of analytics tasks. It is now accessible for organizations choosing to deploy in either a hosted private cloud or an on-premises private cloud with a software-defined infrastructure, making dashDB Local a practical option. From an IT standpoint, it simplifies deployment and management processes by leveraging container technology, which guarantees elastic scalability and easy upkeep. For users, dashDB Local speeds up data collection, customizes analytics for particular use cases, and efficiently translates insights into actionable steps, significantly boosting overall productivity. Furthermore, this all-encompassing strategy enables organizations to better utilize their data than ever before, fostering a culture of informed decision-making.

Apache Doris is a sophisticated data warehouse specifically designed for real-time analytics, allowing for remarkably quick access to large-scale real-time datasets. This system supports both push-based micro-batch and pull-based streaming data ingestion, processing information within seconds, while its storage engine facilitates real-time updates, appends, and pre-aggregations. Doris excels in managing high-concurrency and high-throughput queries, leveraging its columnar storage engine, MPP architecture, cost-based query optimizer, and vectorized execution engine for optimal performance. Additionally, it enables federated querying across various data lakes such as Hive, Iceberg, and Hudi, in addition to traditional databases like MySQL and PostgreSQL. The platform also supports intricate data types, including Array, Map, and JSON, and includes a variant data type that allows for the automatic inference of JSON data structures. Moreover, advanced indexing methods like NGram bloomfilter and inverted index are utilized to enhance its text search functionalities. With a distributed architecture, Doris provides linear scalability, incorporates workload isolation, and implements tiered storage for effective resource management. Beyond these features, it is engineered to accommodate both shared-nothing clusters and the separation of storage and compute resources, thereby offering a flexible solution for a wide range of analytical requirements. In conclusion, Apache Doris not only meets the demands of modern data analytics but also adapts to various environments, making it an invaluable asset for businesses striving for data-driven insights.

A data lakehouse embodies a modern, open architecture tailored for the storage, understanding, and analysis of large data sets. It combines the strong features of traditional data warehouses with the considerable adaptability provided by popular open-source data technologies currently in use. Building a data lakehouse is feasible on Oracle Cloud Infrastructure (OCI), which supports effortless integration with advanced AI frameworks and pre-built AI services, including Oracle’s language processing tools. Users can utilize Data Flow, a serverless Spark service, enabling them to focus on their Spark tasks without the hassle of infrastructure management. Many clients of Oracle seek to create advanced analytics driven by machine learning, applicable to their Oracle SaaS data or other SaaS sources. In addition, our intuitive data integration connectors simplify the setup of a lakehouse, promoting comprehensive analysis of all data alongside your SaaS information and considerably speeding up the solution delivery process. This groundbreaking methodology not only streamlines data governance but also significantly boosts analytical prowess for organizations aiming to harness their data more efficiently. Ultimately, the integration of these technologies empowers businesses to make data-driven decisions with greater agility and insight.

Utilize your data, no matter where it resides, by employing an open and hybrid data lakehouse specifically crafted for AI and analytics applications. Effortlessly combine data from diverse sources and formats, all available through a central access point that includes a shared metadata layer. Boost both cost-effectiveness and performance by matching particular workloads with the most appropriate query engines. Speed up the identification of generative AI insights through integrated natural-language semantic search, which removes the necessity for SQL queries. It's crucial to build your AI applications on reliable data to improve their relevance and precision. Unleash the full potential of your data, regardless of its location. Merging the speed of a data warehouse with the flexibility of a data lake, watsonx.data is designed to promote the growth of AI and analytics capabilities across your organization. Choose the ideal engines that cater to your workloads to enhance your strategy effectively. Benefit from the versatility to manage costs, performance, and functionalities with access to a variety of open engines, including Presto, Presto C++, Spark Milvus, and many others, ensuring that your tools perfectly meet your data requirements. This all-encompassing strategy fosters innovative solutions that can propel your business into the future, ensuring sustained growth and adaptability in an ever-changing market landscape.

Hologres is a versatile cloud-based system that combines serving and analytical processing to seamlessly integrate with the big data ecosystem. It allows users to efficiently analyze and manage vast amounts of data, reaching petabyte scale with impressive concurrency and low latency. By utilizing Hologres, businesses can employ their intelligence tools for multidimensional data analysis, gaining real-time insights into their operations. The platform effectively mitigates challenges often encountered by conventional real-time data warehousing solutions, such as data silos and redundancy issues. It not only caters to the requirements of data migration but also enables the real-time analysis of large data volumes. Remarkably, Hologres can deliver query responses on massive datasets in less than a second, allowing users to engage with their data in a dynamic manner. Furthermore, it supports an impressive number of concurrent writes and queries, achieving up to 100 million transactions per second (TPS), which guarantees that data is readily accessible for analysis immediately after it is recorded. This immediate data availability plays a crucial role in enhancing the overall effectiveness of business analytics and decision-making processes. Moreover, Hologres serves as a reliable solution for organizations looking to streamline their data workflows and improve operational efficiency.

Apache Druid stands out as a robust open-source distributed data storage system that harmonizes elements from data warehousing, timeseries databases, and search technologies to facilitate superior performance in real-time analytics across diverse applications. The system's ingenious design incorporates critical attributes from these three domains, which is prominently reflected in its ingestion processes, storage methodologies, query execution, and overall architectural framework. By isolating and compressing individual columns, Druid adeptly retrieves only the data necessary for specific queries, which significantly enhances the speed of scanning, sorting, and grouping tasks. Moreover, the implementation of inverted indexes for string data considerably boosts the efficiency of search and filter operations. With readily available connectors for platforms such as Apache Kafka, HDFS, and AWS S3, Druid integrates effortlessly into existing data management workflows. Its intelligent partitioning approach markedly improves the speed of time-based queries when juxtaposed with traditional databases, yielding exceptional performance outcomes. Users benefit from the flexibility to easily scale their systems by adding or removing servers, as Druid autonomously manages the process of data rebalancing. In addition, its fault-tolerant architecture guarantees that the system can proficiently handle server failures, thus preserving operational stability. This resilience and adaptability make Druid a highly appealing option for organizations in search of dependable and efficient analytics solutions, ultimately driving better decision-making and insights.

Kinetica is a cloud database designed to effortlessly scale and manage extensive streaming data sets. By leveraging cutting-edge vectorized processors, it significantly accelerates performance for both real-time spatial and temporal tasks, resulting in processing speeds that are orders of magnitude quicker. In a dynamic environment, it enables the monitoring and analysis of countless moving objects, providing valuable insights. The innovative vectorization technique enhances performance for analytics concerning spatial and time series data, even at significant scales. Users can execute queries and ingest data simultaneously, facilitating prompt responses to real-time events. Kinetica’s lockless architecture ensures that data can be ingested in a distributed manner, making it accessible immediately upon arrival. This advanced vectorized processing not only optimizes resource usage but also simplifies data structures for more efficient storage, ultimately reducing the time spent on data engineering. As a result, Kinetica equips users with the ability to perform rapid analytics and create intricate visualizations of dynamic objects across vast datasets. In this way, businesses can respond more agilely to changing conditions and derive deeper insights from their data.

Simcad Pro provides a dynamic platform for visualizing, analyzing, and enhancing process flow systems through an engaging simulation modeling interface. Users can refine, plan, and restructure their workflows and procedures, while also improving layouts, automation, scheduling, and overall facility performance. By incorporating both historical and real-time data, Simcad Pro stands out as one of the premier simulation tools available in the market today. Its applications span a range of industries such as manufacturing, automation and logistics, distribution warehousing, food and beverage, and various service sectors. The software features a robust multi-threaded 64-bit engine that supports real-time adjustments during the simulation process, enabling users to make on-the-fly modifications. Additionally, users can animate their models in 3D, 2D, and virtual reality, utilizing advanced ray tracing, lighting effects, and shadowing techniques. The platform offers a unified model-building environment that employs intelligent, spatially aware agents, facilitates sub-flows, and features collision avoidance capabilities. Furthermore, it includes tools for spaghetti diagrams and congestion analysis, along with heat maps for efficiency and overall equipment effectiveness (OEE). With extensive reporting and analysis functionalities, users can leverage the scenario analyzer to explore various operational scenarios and optimize their systems effectively.

An all-encompassing data virtualization solution for enterprises allows for effortless access to diverse data sources while creating a solid base of datasets and IT-managed data services that cater to nearly any application. The TIBCO® Data Virtualization platform acts as a modern data layer, adeptly addressing the fluctuating needs of organizations that are constantly adapting their architectures. By removing obstacles, it promotes uniformity and encourages the reuse of information by offering on-demand access to all data through a cohesive logical layer that is secure, well-governed, and available to a broad spectrum of users. With immediate access to essential data, organizations can extract actionable insights and react promptly in real-time. Users can conveniently search for and select from a self-service directory of virtualized business data, leveraging their preferred analytics tools to achieve their objectives. This transformation allows them to focus more on analyzing data instead of the labor-intensive process of data extraction. Additionally, this efficient process not only boosts productivity but also empowers teams to make swift and well-informed decisions, ultimately enhancing overall operational effectiveness. The integration of such a system can lead to a more agile and responsive organization, ready to tackle the challenges of a fast-paced business environment.

If you aim to implement a governed delta lake, build a data warehouse, or shift from a traditional database to a modern cloud data infrastructure, Lyftrondata is your ideal solution. The platform allows you to easily create and manage all your data workloads from a single interface, streamlining the automation of both your data pipeline and warehouse. You can quickly analyze your data using ANSI SQL alongside business intelligence and machine learning tools, facilitating the effortless sharing of insights without the necessity for custom coding. This feature not only boosts the productivity of your data teams but also speeds up the process of extracting value from data. By defining, categorizing, and locating all datasets in one centralized hub, you enable smooth sharing with colleagues, eliminating coding complexities and promoting informed, data-driven decision-making. This is especially beneficial for organizations that prefer to store their data once and make it accessible to various stakeholders for ongoing and future utilization. Moreover, you have the ability to define datasets, perform SQL transformations, or transition your existing SQL data processing workflows to any cloud data warehouse that suits your needs, ensuring that your data management approach remains both flexible and scalable. Ultimately, this comprehensive solution empowers organizations to maximize the potential of their data assets while minimizing technical hurdles.

SelectDB is a cutting-edge data warehouse that utilizes Apache Doris, aimed at delivering rapid query analysis on vast real-time datasets. Moving from Clickhouse to Apache Doris enables the decoupling of the data lake, paving the way for an upgraded and more efficient lake warehouse framework. This high-speed OLAP system processes nearly a billion query requests each day, fulfilling various data service requirements across a range of scenarios. To tackle challenges like storage redundancy, resource contention, and the intricacies of data governance and querying, the initial lake warehouse architecture has been overhauled using Apache Doris. By capitalizing on Doris's features for materialized view rewriting and automated services, the system achieves both efficient data querying and flexible data governance approaches. It supports real-time data writing, allowing updates within seconds, and facilitates the synchronization of streaming data from various databases. With a storage engine designed for immediate updates and improvements, it further enhances real-time pre-polymerization of data, leading to better processing efficiency. This integration signifies a remarkable leap forward in the management and utilization of large-scale real-time data, ultimately empowering businesses to make quicker, data-driven decisions. By embracing this technology, organizations can also ensure they remain competitive in an increasingly data-centric landscape.

Manage and safeguard the complete data lifecycle from the Edge to AI across any cloud infrastructure or data center. It operates flawlessly within all major public cloud platforms and private clouds, creating a cohesive public cloud experience for all users. By integrating data management and analytical functions throughout the data lifecycle, it allows for data accessibility from virtually anywhere. It guarantees the enforcement of security protocols, adherence to regulatory standards, migration plans, and metadata oversight in all environments. Prioritizing open-source solutions, flexible integrations, and compatibility with diverse data storage and processing systems, it significantly improves the accessibility of self-service analytics. This facilitates users' ability to perform integrated, multifunctional analytics on well-governed and secure business data, ensuring a uniform experience across on-premises, hybrid, and multi-cloud environments. Users can take advantage of standardized data security, governance frameworks, lineage tracking, and control mechanisms, all while providing the comprehensive and user-centric cloud analytics solutions that business professionals require, effectively minimizing dependence on unauthorized IT alternatives. Furthermore, these features cultivate a collaborative space where data-driven decision-making becomes more streamlined and efficient, ultimately enhancing organizational productivity.

Unify and streamline your data operations. Transform your data ecosystem into a dynamic force. Data Virtuality serves as an integration platform that ensures immediate access to data, centralizes information, and enforces data governance. The Logical Data Warehouse merges both materialization and virtualization techniques to deliver optimal performance. To achieve high-quality data, effective governance, and swift market readiness, establish a single source of truth by layering virtual components over your current data setup, whether it's hosted on-premises or in the cloud. Data Virtuality provides three distinct modules: Pipes Professional, Pipes Professional, and Logical Data Warehouse, which collectively can reduce development time by as much as 80%. With the ability to access any data in mere seconds and automate workflows through SQL, the platform enhances efficiency. Additionally, Rapid BI Prototyping accelerates your time to market significantly. Consistent, accurate, and complete data relies heavily on maintaining high data quality, while utilizing metadata repositories can enhance your master data management practices. This comprehensive approach ensures your organization remains agile and responsive in a fast-paced data environment.

Firebolt delivers remarkable speed and adaptability, enabling users to confront even the toughest data challenges head-on. By innovating the concept of the cloud data warehouse, Firebolt ensures a fast and efficient analytics experience no matter the size of the data involved. This impressive boost in performance allows for the processing of extensive datasets with increased granularity through incredibly quick queries. Users can seamlessly modify their resources to meet varying workloads, data volumes, and numbers of concurrent users. At Firebolt, we strive to enhance the user-friendliness of data warehouses, moving away from traditional complexities. Our dedication to streamlining processes transforms once daunting tasks into simple operations. In contrast to other cloud data warehouse services that benefit from your resource consumption, we embrace a model centered on transparency and fairness. Our pricing framework is designed to facilitate growth without imposing hefty costs, making our solution both effective and budget-friendly. Ultimately, Firebolt equips organizations to fully leverage their data while minimizing the usual obstacles, thereby fostering a more efficient data management experience. This approach not only enhances productivity but also promotes a culture of data-driven decision-making.

This solution, which is fully compatible with Netezza, provides a smooth command-line upgrade option that enhances user experience. It can be utilized in various configurations, including on-premises, cloud-based, or hybrid setups. The IBM® Netezza® Performance Server for IBM Cloud Pak® for Data serves as an advanced platform designed for data warehousing and analytics, effectively addressing the needs of both cloud and on-premises environments. With enhanced in-database analytics capabilities, this next-gen Netezza empowers users to perform data science and machine learning operations on datasets that can scale up to petabytes. Its robust features include failure detection and rapid recovery systems, making it ideal for enterprise applications. Upgrading existing systems is simplified by using a unified command-line interface. Moreover, the platform allows users to query multiple systems as if they were a single entity, enhancing operational efficiency. Users can choose the closest data center or availability zone, define their preferred compute units and storage requirements, and initiate setup with ease. Additionally, the IBM® Netezza® Performance Server is available on IBM Cloud®, Amazon Web Services (AWS), and Microsoft Azure, and it can also be deployed on a private cloud, utilizing the full potential of IBM Cloud Pak for Data System. This adaptability allows organizations to customize their deployment according to their unique requirements and technological infrastructure, ensuring they can optimize their data strategies effectively. Furthermore, with its user-friendly features, businesses can easily scale their operations as needed.

Databend stands out as a pioneering, cloud-centric data warehouse designed for high-speed, cost-efficient analytics tailored for large-scale data processing requirements. Its flexible architecture enables it to adjust seamlessly to fluctuating workloads, thus optimizing resource utilization and minimizing costs. Built using Rust, Databend boasts impressive performance features like vectorized query execution and columnar storage, which significantly improve the speed of data retrieval and processing tasks. The cloud-first design allows for easy integration with a range of cloud services, while also emphasizing reliability, data consistency, and resilience against failures. As an open-source platform, Databend offers a flexible and user-friendly solution for data teams seeking efficient management of big data analytics in cloud settings. Furthermore, its ongoing updates and support from the community guarantee that users are equipped with the most current advancements in data processing technology, ensuring a competitive edge in the rapidly evolving data landscape. This commitment to innovation makes Databend a compelling choice for organizations aiming to harness the full potential of their data.