Top Red Hat JBoss Data Virtualization Alternatives

AWS Glue is a fully managed, serverless solution tailored for data integration, facilitating the easy discovery, preparation, and merging of data for a variety of applications, including analytics, machine learning, and software development. The service incorporates all essential functionalities for effective data integration, allowing users to conduct data analysis and utilize insights in a matter of minutes, significantly reducing the timeline from months to mere moments. The data integration workflow comprises several stages, such as identifying and extracting data from multiple sources, followed by the processes of enhancing, cleaning, normalizing, and merging the data before it is systematically organized in databases, data warehouses, and data lakes. Various users, each with their specific tools, typically oversee these distinct responsibilities, ensuring a comprehensive approach to data management. By operating within a serverless framework, AWS Glue removes the burden of infrastructure management from its users, as it automatically provisions, configures, and scales the necessary resources for executing data integration tasks. This feature allows organizations to concentrate on gleaning insights from their data instead of grappling with operational challenges. In addition to streamlining data workflows, AWS Glue also fosters collaboration and productivity among teams, enabling businesses to respond swiftly to changing data needs. The overall efficiency gained through this service positions companies to thrive in today’s data-driven environment.

Pandora FMS boasts over 50,000 installations worldwide, making it a comprehensive monitoring solution that addresses various traditional monitoring sectors such as servers, networks, applications, logs, synthetic transactions, remote management, and inventory. This platform enables swift identification and resolution of issues, effectively scaling to accommodate both on-premise and multi-cloud environments. With Pandora FMS, users can leverage their entire IT infrastructure and analytical tools to tackle even the most elusive problems. Additionally, it offers extensive control over a wide range of technologies and applications through its collection of more than 500 plugins, which support systems like SAP, Oracle, Lotus, Citrix, Jboss, VMware, AWS, and SQL Server. Consequently, organizations can ensure optimal performance and reliability across their entire technology ecosystem.

JBoss Portal presents a free and open-source option for the development and management of a portal's web interface, user experience, and content. While various commercial portal solutions allow for quick deployment, JBoss Portal distinguishes itself with its no-cost open-source licensing and a highly flexible platform. Developers looking to be part of the Portal project are encouraged to participate in community forums, where they can connect with other contributors. Additionally, exploring the JIRA pages can offer updates on the progress of different project tasks. It's important to recognize that all core developers associated with the JBoss Portal initiative began as independent contributors to other JBoss projects. The process of selecting JBoss core developers is merit-based, ensuring that talented individuals from all around the world are recruited, which promotes diversity within the team. Participating actively in the community not only sharpens your technical abilities but also fosters valuable relationships within the broader open-source community. By collaborating with others, contributors can share knowledge and drive innovation in the portal space.

Red Hat® JBoss® Enterprise Application Platform (JBoss EAP) provides excellent security features, outstanding performance, and scalability that are ideal for a variety of environments. JBoss EAP can be deployed on-premise, in virtualized environments, or over private, public, or hybrid clouds, thus facilitating faster application delivery in all scenarios. The newest version, JBoss EAP 7, is crafted to simplify deployment processes and includes extensive Jakarta EE capabilities, making it versatile for applications across all types of environments. Its cutting-edge modular architecture activates only the necessary services, resulting in improved efficiency. Designed for superior performance and flexibility, JBoss EAP 7 meets the demands of today's dynamic application ecosystems. This architecture, along with a component-driven service model, not only reduces scaling times but also enhances the adaptability of applications across various deployment contexts. By utilizing JBoss EAP, developers can swiftly adjust to the changing requirements of their business operations. Moreover, it is compatible with Jakarta EE and supports a range of web frameworks, including Spring, Spring Web Flow, Spring WS, and Spring Security, thereby ensuring a fluid development experience. Consequently, developers are empowered to create robust applications that can evolve alongside their business needs.

Unlock the full potential of your data, regardless of where it resides. To genuinely adopt a data-centric methodology, it is crucial to tap into the comprehensive array of information available within your organization, encompassing various applications, cloud platforms, and systems. The CONNX data integration solution allows you to effortlessly access, virtualize, and transfer your data—irrespective of its format or source—while preserving the integrity of your existing systems. Make certain that your critical information is strategically positioned to improve service delivery for your organization, clients, partners, and suppliers alike. This innovative solution facilitates the connection and modernization of legacy data sources, converting them from conventional databases into extensive data environments such as Hadoop®, AWS, and Azure®. Additionally, you have the option to migrate aging systems to the cloud for enhanced scalability, transitioning from MySQL to Microsoft® Azure® SQL Database, SQL Server® to Amazon REDSHIFT®, or OpenVMS® Rdb to Teradata®, ensuring your data remains dynamic and easily accessible across all platforms. By implementing these strategies, you can significantly boost the efficiency and effectiveness of your data utilization efforts while remaining adaptable to future technological advancements. This proactive approach helps your organization stay competitive in an increasingly data-driven world.

Oracle Big Data SQL Cloud Service enables organizations to efficiently analyze data across diverse platforms like Apache Hadoop, NoSQL, and Oracle Database by leveraging their existing SQL skills, security protocols, and applications, resulting in exceptional performance outcomes. This service simplifies data science projects and unlocks the potential of data lakes, thereby broadening the reach of Big Data benefits to a larger group of end users. It serves as a unified platform for cataloging and securing data from Hadoop, NoSQL databases, and Oracle Database. With integrated metadata, users can run queries that merge data from both Oracle Database and Hadoop or NoSQL environments. The service also comes with tools and conversion routines that facilitate the automation of mapping metadata from HCatalog or the Hive Metastore to Oracle Tables. Enhanced access configurations empower administrators to tailor column mappings and effectively manage data access protocols. Moreover, the ability to support multiple clusters allows a single Oracle Database instance to query numerous Hadoop clusters and NoSQL systems concurrently, significantly improving data accessibility and analytical capabilities. This holistic strategy guarantees that businesses can derive maximum insights from their data while maintaining high levels of performance and security, ultimately driving informed decision-making and innovation. Additionally, the service's ongoing updates ensure that organizations remain at the forefront of data technology advancements.

GitBucket is a web-based Git platform developed with the Scala programming language. Moreover, users can deploy the GitBucket WAR file on any servlet container that supports Servlet 3.0, including options like Jetty, Tomcat, and JBoss. This level of adaptability provides users with numerous deployment possibilities, making it suitable for different server configurations. Ultimately, this versatility enhances the overall user experience by accommodating diverse operational needs.

Dremio offers rapid query capabilities along with a self-service semantic layer that interacts directly with your data lake storage, eliminating the need to transfer data into exclusive data warehouses, and avoiding the use of cubes, aggregation tables, or extracts. This empowers data architects with both flexibility and control while providing data consumers with a self-service experience. By leveraging technologies such as Apache Arrow, Data Reflections, Columnar Cloud Cache (C3), and Predictive Pipelining, Dremio simplifies the process of querying data stored in your lake. An abstraction layer facilitates the application of security and business context by IT, enabling analysts and data scientists to access and explore data freely, thus allowing for the creation of new virtual datasets. Additionally, Dremio's semantic layer acts as an integrated, searchable catalog that indexes all metadata, making it easier for business users to interpret their data effectively. This semantic layer comprises virtual datasets and spaces that are both indexed and searchable, ensuring a seamless experience for users looking to derive insights from their data. Overall, Dremio not only streamlines data access but also enhances collaboration among various stakeholders within an organization.

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.

Oracle Data Service Integrator enables organizations to quickly establish and manage federated data services, providing a seamless way to access various datasets. Built entirely on industry standards, this tool is designed to be declarative and encourages the reuse of data services. It uniquely serves as the only data federation solution that allows for the creation of bidirectional data services that support both reading and writing across multiple data sources. In addition, it features a groundbreaking capability that eliminates the need for coding, allowing users to graphically design both simple and complex adjustments to different data sources with ease. Users benefit from straightforward installation, validation, uninstallation, upgrading, and initiation processes with the Data Service Integrator. Originally known as Liquid Data and AquaLogic Data Services Platform (ALDSP), Oracle Data Service Integrator still includes some elements from these previous titles in its product architecture, installation paths, and components. This approach provides continuity for users who are accustomed to the legacy names, facilitating a smooth navigation experience within the system while enhancing overall functionality. As a result, organizations can maximize their data integration capabilities efficiently and effectively.

The Opensource Website Framework goes beyond a conventional web development framework by providing the freedom to choose your preferred framework. With the help of the JBoss Portlet Bridge, you can either create new JSF applications or seamlessly integrate existing ones into GateIn projects. The recently released PortletBridge 2 offers compatibility with JSF 1.2 and RichFaces 3, facilitating the creation of portlets. In addition, version 3.0 has been tailored to work with JSF2, while the upcoming 3.1 versions will ensure support for RichFaces 4, thereby broadening the array of capabilities for developers. This versatility not only enhances the development process but also significantly improves the overall functionality of web applications, making it a highly attractive choice for developers aiming to elevate their projects.

The core technology driving modern data integration and management solutions is engineered to quickly connect a variety of both structured and unstructured data sources. This technology facilitates the thorough cataloging of your entire data landscape, ensuring that information stays within its original repositories and is accessed only when necessary, thus removing the need for redundant copies. Users have the ability to create data models that suit their specific requirements, even when utilizing diverse data sources, while simultaneously keeping the complexities of backend systems hidden from the end users. Access to the virtual model is securely provided through standard SQL as well as other formats like REST, SOAP, and OData, making it easier to reach a wide range of data types. It boasts comprehensive capabilities for data integration and modeling, supplemented by an Active Data Catalog that supports self-service for exploring and preparing data and metadata. In addition, this technology includes strong measures for data security and governance, ensures quick and intelligent execution of data queries, and offers real-time delivery of data in multiple formats. The solution also encourages the creation of data marketplaces and effectively separates business applications from data systems, which fosters more informed, data-driven decision-making processes. As a result, this cutting-edge approach significantly improves the agility and responsiveness of organizations in managing their data resources, allowing them to adapt swiftly to changing business needs. Ultimately, it empowers businesses to leverage their data assets more effectively than ever before.

Traditional methods for integrating mainframe data, like ETL, data warehouses, and connector development, are becoming increasingly insufficient in terms of speed, accuracy, and efficiency in the current business environment. With the ever-growing volume of data generated and stored on mainframes, these timeworn approaches are increasingly outpaced. Data virtualization presents itself as a modern solution to this widening gap, streamlining the access of mainframe data for both developers and applications. This innovative method enables organizations to identify and map their data just once, allowing for easy virtualization and reuse across multiple platforms. Consequently, this capability ensures that data remains in alignment with overarching business objectives and goals. By implementing data virtualization on z/OS, organizations can effectively navigate the complexities associated with mainframe resources. Furthermore, data virtualization promotes the integration of information from various disparate sources into a unified logical repository, which significantly enhances the connection between mainframe data and distributed applications. In addition, this technique allows for the enrichment of mainframe data through the incorporation of insights derived from location, social media, and other external datasets, leading to a more holistic understanding of business dynamics. As organizations seek to remain competitive, embracing such advanced methodologies can foster agility and innovation in decision-making processes.

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.

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.

Adaptive Data Virtualization™ technology allows organizations to run their existing applications on modern cloud data warehouses with minimal changes or configuration. By utilizing Datometry Hyper-Q™, companies can quickly adopt new cloud databases, effectively control ongoing operational expenses, and improve their analytical capabilities, thereby hastening their digital transformation initiatives. This virtualization software from Datometry enables any legacy application to operate on any cloud database, promoting seamless interoperability between applications and various databases. As a result, businesses can choose their desired cloud database without the risk of dismantling, rewriting, or replacing their current applications. Moreover, it guarantees runtime compatibility for applications by emulating and transforming the functionalities of traditional data warehouses. This innovative solution can be easily implemented across major cloud platforms such as Azure, AWS, and GCP. Furthermore, applications can utilize existing JDBC, ODBC, and native connectors without needing modifications, ensuring a seamless transition to cloud environments. It also facilitates connections with prominent cloud data warehouses, including Azure Synapse Analytics, AWS Redshift, and Google BigQuery, which enhances opportunities for data integration and comprehensive analysis. With these capabilities, organizations are better positioned to leverage cloud technologies and drive business innovation.

Quickly set up cloud environments customized for immediate development, testing, and improved efficiency for both IT and business teams. Reduce the risks and costs linked to managing your data lake by implementing strong data governance practices, which include thorough end-to-end data lineage for business users. Enhance cost-effectiveness by ensuring your data lakes, data warehouses, or big data projects are fed with clean, dependable, and timely data, while also streamlining applications and retiring outdated databases. Take advantage of automatic schema propagation to speed up job creation, incorporate type-ahead search capabilities, and ensure backward compatibility, all within a design that supports execution across diverse platforms. Create data integration workflows and uphold governance and quality standards through an easy-to-use design that tracks and suggests usage trends, thereby improving user experience. Additionally, increase visibility and information governance by providing complete and authoritative insights into your data, supported by proof of lineage and quality, which allows stakeholders to make well-informed decisions based on precise information. By implementing these strategies, organizations can cultivate a more adaptable and data-centric culture, ultimately driving innovation and growth. This approach not only empowers teams but also aligns business objectives with data-driven decisions.

Accelerate the development of AI innovations with the cloud-native data integration solutions provided by IBM Cloud Pak for Data. With AI-enhanced data integration functionalities available from any location, the impact of your AI and analytics initiatives is closely tied to the caliber of the underlying data. Leveraging a contemporary container-based framework, IBM® DataStage® within IBM Cloud Pak® for Data guarantees the provision of high-quality data. This offering combines exceptional data integration with DataOps, governance, and analytics into a cohesive data and AI ecosystem. By streamlining administrative processes, it contributes to a reduction in total cost of ownership (TCO). The platform's AI-driven design accelerators, in conjunction with readily available integrations for DataOps and data science services, significantly expedite the pace of AI development. Moreover, its capabilities for parallel processing and multicloud integration facilitate the delivery of consistent data across extensive hybrid or multicloud environments. Additionally, the IBM Cloud Pak for Data platform allows for the effective management of the complete data and analytics lifecycle, incorporating a range of services such as data science, event messaging, data virtualization, and data warehousing, all supported by a parallel engine and automated load balancing. This all-encompassing strategy equips your organization to remain at the forefront of the swiftly changing data and AI landscape, ensuring that you can adapt and thrive in a competitive market.

SAP HANA is a cutting-edge in-memory database that efficiently manages both transactional and analytical workloads by utilizing a single data copy, regardless of its nature. It effectively eliminates the divide between transactional and analytical functions within businesses, allowing for quick decision-making whether used in a traditional data center or through cloud services. This advanced database management system grants users the ability to develop intelligent, real-time applications, which promotes fast decision-making from a consolidated data repository. By integrating sophisticated analytics, it bolsters the performance of modern transaction processing systems. Organizations can leverage cloud-native features such as enhanced scalability, speed, and performance to create comprehensive data solutions. With SAP HANA Cloud, businesses gain access to dependable and actionable insights from a unified platform while maintaining stringent security, privacy, and data anonymization that align with established enterprise standards. In the rapidly evolving market landscape, the intelligent enterprise increasingly depends on prompt insights generated from data, highlighting the necessity for real-time access to critical information. As organizations face rising expectations for immediate insights, adopting a powerful database solution like SAP HANA is essential for maintaining a competitive edge. The ability to make informed decisions based on real-time data is becoming a key differentiator in business success.

ORMIT™, Jasper stands out as the exclusive automated solution that transitions Oracle Reports into Jasper Reports without any hassle. By utilizing this technology, users can potentially reduce their upgrade time by as much as 90% compared to traditional manual methods. Additionally, RENAPS ORMIT™ Jasper effectively mitigates the risks associated with manual migration processes. This innovative tool not only enhances code quality but also improves maintainability, resulting in further cost efficiencies over time. Reports that are transitioned through this system are guaranteed to be entirely open source, eliminating concerns about licensing fees, vendor lock-in, or ongoing support costs. Furthermore, Jasper Reports is designed to be compatible with any JavaEE server, such as Tomcat or JBoss, and maintains versatility for use in non-Java application development as well. This seamless integration makes ORMIT™, Jasper an invaluable asset for businesses looking to modernize their reporting systems.

Hammerspace is an innovative storage solution that unlocks the vast amounts of fast local NVMe storage inside GPU servers, turning what was previously stranded capacity into a new ultra-fast storage tier that accelerates AI training and checkpointing. Designed to overcome the limitations of expensive and complex legacy storage systems, Hammerspace enables consistently high GPU utilization by providing low-latency, parallel access to data across thousands of servers simultaneously. The platform’s global data architecture is built on standard NFS protocols, eliminating the need for proprietary clients and simplifying integration with existing Linux storage servers and hybrid cloud environments. By orchestrating data movement between on-premises and cloud infrastructure, Hammerspace supports flexible AI workflows that maximize resource usage and minimize power consumption. Hammerspace has been proven through MLPerf benchmarks to deliver scalable, linear performance gains, dramatically speeding up checkpointing times by 10 to 100 times. Trusted by industry leaders like Meta and Los Alamos National Laboratory, it helps reduce external storage costs, power usage, and rack space requirements. The platform’s intuitive interface and rapid deployment allow organizations to bring petabytes of capacity online within days and start accelerating AI workloads immediately. Its hyperscale NAS architecture ensures consistent throughput and low latency at scale, critical for large machine learning projects. By transforming idle GPU server storage into a shared, protected resource, Hammerspace redefines cost efficiency and performance in AI infrastructure. This technology empowers data-driven organizations to innovate faster, reduce their energy footprint, and optimize their AI investment returns.

A wide array of products exists to support businesses in achieving their objectives, but for organizations aiming to cultivate a data-driven culture while optimizing efficiency and reducing expenses, Fraxses stands out as the premier distributed data platform globally. With Fraxses, clients gain instant access to data, unlocking valuable insights through a solution that can implement either a data mesh or a data fabric architecture. Visualize a data mesh as a framework that interconnects diverse data sources, enabling them to function seamlessly as one integrated entity. Unlike other platforms that primarily focus on data integration and virtualization, Fraxses offers a decentralized architecture that distinguishes it from competitors. While Fraxses effectively supports traditional data integration techniques, the trend is shifting toward an innovative model where data is delivered directly to users, thereby negating the need for a centralized data lake or platform. This forward-thinking approach not only empowers users with greater autonomy but also enhances the ease of data access throughout the organization, fostering a more agile and responsive data environment. As businesses continue to evolve, embracing such innovative solutions becomes crucial for maintaining a competitive edge in the market.

Enhance the efficiency of self-service provisioning and refreshing of enterprise workloads by effectively integrating with your existing toolchain. Equip data scientists with superior data delivery options and the opportunity for reuse through a comprehensive array of APIs and automation features. Guarantee the capability to access any data across various cloud environments at any time, all while maintaining scalability that outperforms conventional solutions. Mitigate the risk of business interruptions stemming from ransomware or cyber threats by facilitating swift recovery through the use of immutable backups. Present a unified platform that boosts the protection, security, retention, governance, and recovery of your data, regardless of whether it resides on-premises or within the cloud. Actifio’s groundbreaking software platform converts data silos into streamlined data pipelines, improving both access and utilization. The Virtual Data Pipeline (VDP) offers extensive data management across on-premises, hybrid, or multi-cloud frameworks, delivering strong application integration, SLA-driven orchestration, flexible data movement, along with enhanced immutability and security features. This comprehensive strategy empowers organizations to refine their data approach, ensuring resilience against a range of data-related threats while adapting to evolving business needs. By adopting such a holistic solution, companies can not only safeguard their information but also unlock new opportunities for innovation and growth.

Clonetab provides a variety of solutions tailored to the specific requirements of different sites. While the essential features of Clonetab are adequate for the majority of site needs, it also includes the capability to incorporate custom steps, enhancing its adaptability for unique circumstances. The base module for Clonetab supports Oracle Databases, eBusiness Suite, and PeopleSoft. Traditional shell scripts used for performing refreshes often pose security risks by leaving sensitive passwords in plain files and typically lack an effective audit trail to monitor who executes the refreshes and for what reasons. This situation complicates the maintenance of these scripts, particularly when the original creators are no longer part of the organization. Clonetab addresses this issue by enabling the automation of refresh processes. With functionalities like pre, post, and random scripts, as well as instance retention options for dblinks, concurrent processes, and appltop binary copying, Clonetab empowers users to automate the majority of their refresh tasks efficiently. These automated processes can be executed only once, allowing for easy scheduling thereafter. Overall, Clonetab streamlines the management of refreshes, significantly reducing manual effort and enhancing security.

Create federated identifiers for source data to enable users to effortlessly connect to diverse data sources. Implement a web-based administrative interface to facilitate the management of user permissions, access levels, and authorizations for improved oversight. Integrate enhancements for data quality, such as generating match-codes and implementing parsing functions, to guarantee data integrity. Boost overall performance by utilizing in-memory caching and effective scheduling techniques. Safeguard sensitive data through advanced masking and encryption strategies. This methodology ensures that application queries remain current and accessible to users while reducing the load on operational systems. You can configure access rights at various levels—catalog, schema, table, column, and row—providing customized security solutions. The sophisticated features for data masking and encryption not only control visibility but also dictate the specific elements of data that users can view, significantly minimizing the likelihood of sensitive information breaches. In conclusion, these integrated functionalities work in harmony to cultivate a secure and highly efficient data management framework that caters to the needs of users while maintaining stringent security standards.

A significant challenge in enhancing AI-fueled decision-making is the insufficient use of available data. IBM Cloud Pak® for Data offers an integrated platform featuring a data fabric that facilitates easy connection and access to disparate data, regardless of whether it is stored on-premises or in multiple cloud settings, all without the need to move the data. It optimizes data accessibility by automatically detecting and categorizing data to deliver useful knowledge assets to users, while also enforcing automated policies to ensure secure data utilization. To accelerate insight generation, this platform includes a state-of-the-art cloud data warehouse that integrates seamlessly with current systems. Additionally, it enforces universal data privacy and usage policies across all data sets, ensuring ongoing compliance. By utilizing a high-performance cloud data warehouse, businesses can achieve insights more swiftly. The platform also provides data scientists, developers, and analysts with an all-encompassing interface to build, deploy, and manage dependable AI models across various cloud infrastructures. Furthermore, you can enhance your analytical capabilities with Netezza, which is a powerful data warehouse optimized for performance and efficiency. This holistic strategy not only expedites decision-making processes but also encourages innovation across diverse industries, ultimately leading to more effective solutions and improved outcomes.

Embedded Data Virtualization empowers applications by offering seamless data connectivity. The CData Query Federation Drivers act as a comprehensive data access layer, simplifying the development of applications and facilitating data retrieval. With just one interface, users can execute SQL queries to access information from over 250 different applications and databases. This driver delivers robust features such as: a unified SQL language and API to interact with various SaaS, NoSQL, relational, and Big Data sources; the ability to merge data from multiple origins without the need for ETL processes; enhanced performance through intelligent push-down in federated queries; and support for more than 250 connections, thanks to the user-friendly CData Drivers. Overall, this solution streamlines the process of data management and integration for developers across diverse platforms.

WildFly is recognized as a powerful, adaptable, and lightweight application server that supports the creation of outstanding applications. Its centralized configuration system is designed with an emphasis on simplicity and enhancing user experience. The configuration is organized into intuitive subsystems, which effectively hide the internal wiring of the server from the user. Management options are seamlessly integrated, offering various access methods such as a command-line interface (CLI), a web-based administration portal, a native Java API, an HTTP/JSON REST API, and a JMX gateway. This diverse range of access points allows users to automate their workflows using their preferred tools and programming languages. Moreover, WildFly utilizes JBoss Modules to maintain true application isolation, shielding server implementation specifics from applications while only connecting to the essential JAR files. The visibility rules come with sensible defaults that can be customized, providing added flexibility for developers. Additionally, the advanced dependency resolution algorithm ensures that classloading performance is consistent, regardless of how many library versions are installed, thereby enhancing the development experience. Consequently, users benefit from a streamlined integration process that facilitates the application development journey within the WildFly framework, making it a compelling choice for modern software development.

K2View is committed to empowering enterprises to fully utilize their data for enhanced agility and innovation. Our Data Product Platform facilitates this by generating and overseeing a reliable dataset for each business entity as needed and in real-time. This dataset remains continuously aligned with its original sources, adjusts seamlessly to changes, and is readily available to all authorized users. We support a variety of operational applications, such as customer 360, data masking, test data management, data migration, and the modernization of legacy applications, enabling businesses to achieve their goals in half the time and at a fraction of the cost compared to other solutions. Additionally, our approach ensures that organizations can swiftly adapt to evolving market demands while maintaining data integrity and security.

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.