Top 10 Alternatives to Red Hat jBoss Data Virtualization Recently Reviewed By G2 Community
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SAP HANA Cloud is the cloud-native data foundation of SAP Business Technology Platform, it stores, processes and analyzes data in real time at petabyte scale and converges multiple data types in a single system while managing it more efficiently with integrated multitier storage.
Self-service data discovery. Fastest to actionable insight. Collaborative, predictive, event-driven data analysis - free from IT.
A next-generation iPaaS, reimagined for new hybrid data management challenges with a microservices architecture.
Denodo provides performance and unified access to the broadest range of enterprise, Big Data, cloud and unstructured sources.
AWS Glue is a fully managed extract, transform, and load (ETL) service designed to make it easy for customers to prepare and load their data for analytics.
lyftrondata modern data hub combines an effortless data hub with agile access to data sources. Lyftron eliminates traditional ETL/ELT bottlenecks with automatic data pipeline and make data instantly accessible to BI user with the modern cloud compute of Spark & Snowflake. Lyftron connectors automatically convert any source into normalized, ready-to-query relational format and provide search capability on your enterprise data catalog.
FME Platform lets you connect and transform spatial data. Build workspaces in a few quick clicks using FME's drag-and-drop interface. Workspaces are repeatable and can be run again and again. No coding is required, which means you can spend more time using your data and less time fighting with it (And if you really want, FME Desktop also supports Python).
An enterprise data virtualization solution that orchestrates access to multiple and varied data sources and delivers the data sets and IT-curated data services foundation for nearly any analytics solution
IBM Netezza Performance Server is a purpose-built, standards-based data warehouse and analytics appliance that integrates database, server, storage and analytics into an easy-to-manage system. It is designed for high-speed analysis of big data volumes, scaling into the petabytes.
Oracle VM reduces operations and support costs while increasing IT efficiency and agility on premises and in the cloud.