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Ratings and Reviews 0 Ratings
Alternatives to Consider
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Google Cloud BigQueryBigQuery 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.
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DashboardFoxDashboardFox is a powerful tool for business users, providing features like dashboards, interactive visualizations, codeless reporting, data security, mobile access, and scheduled reports. Unlike many other software options, DashboardFox operates on a one-time payment model, allowing users to purchase the software outright without the burden of ongoing subscription fees. It can be conveniently installed on your own server, ensuring that your data remains secure behind your firewall, while also offering managed hosting for those interested in Cloud BI—maintaining your ownership of data and licenses. With DashboardFox, users can easily interact with live data visualizations and create new reports without needing any technical expertise, thanks to its intuitive codeless builder. This makes it a compelling alternative to popular platforms like Tableau, Sisense, Looker, Domo, Qlik, and Crystal Reports, providing similar functionalities with added advantages. Whether you are a small business or a large enterprise, DashboardFox adapts to your needs, making data handling more efficient and accessible for everyone involved.
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SnowflakeSnowflake is a comprehensive, cloud-based data platform designed to simplify data management, storage, and analytics for businesses of all sizes. With a unique architecture that separates storage and compute resources, Snowflake offers users the ability to scale both independently based on workload demands. The platform supports real-time analytics, data sharing, and integration with a wide range of third-party tools, allowing businesses to gain actionable insights from their data quickly. Snowflake's advanced security features, including automatic encryption and multi-cloud capabilities, ensure that data is both protected and easily accessible. Snowflake is ideal for companies seeking to modernize their data architecture, enabling seamless collaboration across departments and improving decision-making processes.
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StarTreeStarTree Cloud functions as a fully-managed platform for real-time analytics, optimized for online analytical processing (OLAP) with exceptional speed and scalability tailored for user-facing applications. Leveraging the capabilities of Apache Pinot, it offers enterprise-level reliability along with advanced features such as tiered storage, scalable upserts, and a variety of additional indexes and connectors. The platform seamlessly integrates with transactional databases and event streaming technologies, enabling the ingestion of millions of events per second while indexing them for rapid query performance. Available on popular public clouds or for private SaaS deployment, StarTree Cloud caters to diverse organizational needs. Included within StarTree Cloud is the StarTree Data Manager, which facilitates the ingestion of data from both real-time sources—such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda—and batch data sources like Snowflake, Delta Lake, Google BigQuery, or object storage solutions like Amazon S3, Apache Flink, Apache Hadoop, and Apache Spark. Moreover, the system is enhanced by StarTree ThirdEye, an anomaly detection feature that monitors vital business metrics, sends alerts, and supports real-time root-cause analysis, ensuring that organizations can respond swiftly to any emerging issues. This comprehensive suite of tools not only streamlines data management but also empowers organizations to maintain optimal performance and make informed decisions based on their analytics.
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dRevealdReveal enhances the process of data visualization and reporting for organizations of any scale. By integrating it effortlessly into your existing product, you can access a dynamic and scalable solution: Create Comprehensive Reports: Utilize our user-friendly builder to design intricate grids, interactive dashboards, and professional documents tailored to your requirements. Streamlined User Access: Business users can interact with reports directly within your product, which reduces the need for switching applications and enhances overall user satisfaction. dReveal transcends traditional static data presentations: Dynamic Visualizations: Develop stunning, interactive reports that enable users to examine data from multiple perspectives, fostering a deeper comprehension of insights. Adaptability & Management: Export reports in diverse formats and set up automated deliveries to ensure that all stakeholders remain updated. With dReveal, you can scale alongside your organization: It integrates effortlessly with products of any size, adjusting to meet your unique demands. Empower your users and unlock valuable data insights, all while operating within the familiar framework of your product. Opt for dReveal to elevate your data reporting experience.
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AnalyticsCreatorEnhance your data initiatives with AnalyticsCreator, which simplifies the design, development, and implementation of contemporary data architectures, such as dimensional models, data marts, and data vaults, or blends of various modeling strategies. Easily connect with top-tier platforms including Microsoft Fabric, Power BI, Snowflake, Tableau, and Azure Synapse, among others. Enjoy a more efficient development process through features like automated documentation, lineage tracking, and adaptive schema evolution, all powered by our advanced metadata engine that facilitates quick prototyping and deployment of analytics and data solutions. By minimizing tedious manual processes, you can concentrate on deriving insights and achieving business objectives. AnalyticsCreator is designed to accommodate agile methodologies and modern data engineering practices, including continuous integration and continuous delivery (CI/CD). Allow AnalyticsCreator to manage the intricacies of data modeling and transformation, thus empowering you to fully leverage the capabilities of your data while also enjoying the benefits of increased collaboration and innovation within your team.
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DataBuckEnsuring the integrity of Big Data Quality is crucial for maintaining data that is secure, precise, and comprehensive. As data transitions across various IT infrastructures or is housed within Data Lakes, it faces significant challenges in reliability. The primary Big Data issues include: (i) Unidentified inaccuracies in the incoming data, (ii) the desynchronization of multiple data sources over time, (iii) unanticipated structural changes to data in downstream operations, and (iv) the complications arising from diverse IT platforms like Hadoop, Data Warehouses, and Cloud systems. When data shifts between these systems, such as moving from a Data Warehouse to a Hadoop ecosystem, NoSQL database, or Cloud services, it can encounter unforeseen problems. Additionally, data may fluctuate unexpectedly due to ineffective processes, haphazard data governance, poor storage solutions, and a lack of oversight regarding certain data sources, particularly those from external vendors. To address these challenges, DataBuck serves as an autonomous, self-learning validation and data matching tool specifically designed for Big Data Quality. By utilizing advanced algorithms, DataBuck enhances the verification process, ensuring a higher level of data trustworthiness and reliability throughout its lifecycle.
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Fraud.netFraud.net stands as the premier framework for managing fraud, utilizing an advanced collective intelligence network, cutting-edge AI, and a state-of-the-art cloud platform that empowers users to: * Integrate fraud data from various sources with a single connection * Identify fraudulent transactions in real-time with an accuracy rate exceeding 99.5% * Reveal valuable insights hidden within vast amounts of data to enhance fraud management strategies Acknowledged in Gartner's market guide for online fraud detection, Fraud.net offers a robust, real-time solution for fraud prevention and analytics specifically designed to meet the demands of businesses. It serves as a centralized command hub, merging data from multiple sources and systems while monitoring digital identities and behaviors, ultimately employing the latest technologies to eliminate fraudulent activities and facilitate secure transactions. Reach out to us today to start your free trial and experience our services firsthand, ensuring your business is protected against potential fraud.
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SatoriSatori is an innovative Data Security Platform (DSP) designed to facilitate self-service data access and analytics for businesses that rely heavily on data. Users of Satori benefit from a dedicated personal data portal, where they can effortlessly view and access all available datasets, resulting in a significant reduction in the time it takes for data consumers to obtain data from weeks to mere seconds. The platform smartly implements the necessary security and access policies, which helps to minimize the need for manual data engineering tasks. Through a single, centralized console, Satori effectively manages various aspects such as access control, permissions, security measures, and compliance regulations. Additionally, it continuously monitors and classifies sensitive information across all types of data storage—including databases, data lakes, and data warehouses—while dynamically tracking how data is utilized and enforcing applicable security policies. As a result, Satori empowers organizations to scale their data usage throughout the enterprise, all while ensuring adherence to stringent data security and compliance standards, fostering a culture of data-driven decision-making.
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RaimaDBRaimaDB is an embedded time series database designed specifically for Edge and IoT devices, capable of operating entirely in-memory. This powerful and lightweight relational database management system (RDBMS) is not only secure but has also been validated by over 20,000 developers globally, with deployments exceeding 25 million instances. It excels in high-performance environments and is tailored for critical applications across various sectors, particularly in edge computing and IoT. Its efficient architecture makes it particularly suitable for systems with limited resources, offering both in-memory and persistent storage capabilities. RaimaDB supports versatile data modeling, accommodating traditional relational approaches alongside direct relationships via network model sets. The database guarantees data integrity with ACID-compliant transactions and employs a variety of advanced indexing techniques, including B+Tree, Hash Table, R-Tree, and AVL-Tree, to enhance data accessibility and reliability. Furthermore, it is designed to handle real-time processing demands, featuring multi-version concurrency control (MVCC) and snapshot isolation, which collectively position it as a dependable choice for applications where both speed and stability are essential. This combination of features makes RaimaDB an invaluable asset for developers looking to optimize performance in their applications.
What is Fortra Sequel?
Sequel delivers customized business intelligence solutions specifically designed for Power Systems™ that function on IBM i platforms. Its powerful querying and reporting features make it easier to access, analyze, and share data in a manner that aligns with individual preferences and requirements. Sequel is a budget-friendly option for business intelligence on IBM i, appealing to a diverse audience that includes IT specialists, business users, and top executives. Presently, numerous clients worldwide depend on Sequel to acquire essential data exactly when they need it. IT teams can quickly implement the software, smoothly transition existing queries from Query/400, and provide data to end users at impressive speeds. Additionally, the intuitive interfaces provided by Sequel—including the classic green screen, the graphical Sequel Viewpoint interface, and various web-based options—allow IT departments to equip business users and executives with straightforward access to data, enabling them to tackle urgent inquiries more effectively. The evolution of iSeries reporting has become significantly simpler and more user-friendly. This transformation not only optimizes operations but also cultivates a culture centered around data within organizations, ultimately enhancing decision-making processes across all levels.
What is Apache Druid?
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.
Integrations Supported
Acryl Data
Amazon Web Services (AWS)
Apache Airflow
Apache Kafka
Apache Superset
Astro
Azure Marketplace
DataHub
Deep.BI
Emgage
Integrations Supported
Acryl Data
Amazon Web Services (AWS)
Apache Airflow
Apache Kafka
Apache Superset
Astro
Azure Marketplace
DataHub
Deep.BI
Emgage
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Fortra
Date Founded
1982
Company Location
United States
Company Website
www.fortra.com/product-lines/sequel
Company Facts
Organization Name
Druid
Date Founded
2013
Company Website
druid.apache.org/technology
Categories and Features
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Data Visualization
Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge
Categories and Features
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge
Relational Database
ACID Compliance
Data Failure Recovery
Multi-Platform
Referential Integrity
SQL DDL Support
SQL DML Support
System Catalog
Unicode Support
