In-memory Database

Exasol v6: Pluggable language support

14 Oct 2016 | Share

As part of our article series, today we cover Pluggable language support. New feature focusing ease-of use:

Among programmers and developers, the languages and tools in use for projects can vary substantially. In the business intelligence ecosystem, SQL long represented the gold standard for data processing. Data scientists, on the other hand, spend much of their days working with R and Python. With Exasol v6, we want to offer users even more options for the Exasol high-performance data processing architecture without making it necessary to learn a new programming language.

Aside from out-of-the-box support for R, Python, Java and Lua, Exasol v6 now includes a framework for integrating the programming language of your choice. Better yet, with v6, users can now even use multiple versions of a language in parallel. New languages can be installed easily and can be immediately put to use in Exasol for in-database-analytics. Exasol runs the programs fully automated on a cluster in parallel to ensure optimal scalability and performance. With v6, data practitioners are finally only limited by creativity and not by the amount of programming languages they know.

Parallel Execution Pipeline Exasol v6

Parallel Execution Pipeline Exasol v6

Key advantages of pluggable language support:

  • Use any programming language and corresponding version of your choice
  • Run in-database analytics on a parallel in-memory cluster exactly where the data resides
  • Combine traditional SQL with new data science methods

Stay tuned for tomorrows installment on improved Hadoop integration and extended connectivity with WebSocket.

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