Apache Spark powers live SQL analytics in SnappyData

The team behind Pivotal’s GemFire in-memory transactional data store recently unveiled a new database solution powered by GemFire and Apache Spark, called SnappyData.

SnappyData is another example of the way Spark has recently been employed as a component in a larger database solution, with or without other components from Apache Hadoop.

Snap and spark

SnappyData — which is the name of both the new database and the organization producing it — was built to span two worlds. It uses the Apache Spark in-memory data-analytics engine so it can perform live SQL analytics on both static datasets and streams. Queries against SnappyData can be written as conventional SQL or as Spark abstractions, so existing work done in both paradigms can be re-used, alone or together, on the same data.

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