Our release is now live & open source!
Introducing SnappyData
A new real-time analytics platform that combines probabilistic data structures, approximate query processing and in memory distributed data management to deliver powerful analytic querying and alerting capabilities on Apache Spark at a fraction of the cost of traditional big data analytics platforms. Learn more
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OLTP + OLAP Inside Spark
Instantaneous analysis on streaming data, written to a data store that support high writes, point updates, point queries as well as analytic queries.
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Spark & SQL interfaces
SnappyData delivers ease of use by exposing the Spark programming model and SQL query execution.
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Synopsis Data Structures
Data structures with very low memory footprint designed for fast approximate querying.
How does it work?
SnappyData fuses the Spark computational engine with a highly available, multi-tenanted in-memory database to execute OLAP & OLTP queries on streaming data. Further, SnappyData can store data in a variety of synopsis data structures to provide extremely fast responses on less resources. Finally, applications can either submit Spark programs or connect using JDBC/ODBC to run interactive or continuous SQL queries. Learn more
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1
Deploy SnappyData and connect it to historical or streaming data
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Write interactive or continuous SQL queries on connected data
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Use SnappyData’s synopsis structures to speed up execution
SnappyData Features
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Committed to Open Source
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SQL & Spark interfaces
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Concurrent OLAP+OLTP workloads
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Synopsis data structures designed for speed
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Integration with Spark ecosystem
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Always-on high availability
SnappyData Team
Snappydata was incubated at Pivotal by a highly experienced team of engineers empowered to create a breakthrough OSS Big Data platform. That team spun out in Jan 2016 as a standalone entity. Learn more
Download our open source release
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