EXASOL announced new, even faster release of its already world fastest in-memory analytical database version 6.0. Faster join, insert & delete, backup & recovery, cluster resizing is just a small list of the performance improvements.
But the performance is just one of many improvements.
Other important ones are:
- Data virtualization framework with virtual schemas
Transparent access to data from various data sources. Analyze data without moving it into EXASOL. Since data remains in source systems, you are avoid data duplication and complex ETL jobs and still have access to the latest information.
- High-performance data integration framework
A common integration framework for virtualized data access and imports allows you easy implementation and customization of any data source adapter on demand and share with other users via GitHub.
- Increased support for Hadoop
Hadoop-based data stored in any HCatalog-supported native data format is now instantly available for analytics in EXASOL through the new data integration framework. Data access is fully parallelized for maximum throughput.
- Pluggable language support
EXASOL V6 offers a framework to integrate any analytical programming language. You can package up the programming language of your choice, deploy it to your instance of EXASOL and use it for in-database analytics as an extension of already broad out-of-the-box support for R, Python, Java and Lua.
- Advanced automation
Administrators can completely automate almost all installation and configuration tasks through an easy-to-use API without manual intervention.
- Improved connectivity
EXASOL V6 offers a JSON-based web socket API alongside current support for ODBC, JDBC and .NET. With the API, virtually every platform can be easily connected to EXASOL based on a simple wrapper-like driver or direct web socket connection. Also, a native lightweight Python driver based on this API has been included in EXASOL V6.
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