What is SnappyData used for?

SnappyData, also called TIBCO ComputeDB, is an in-memory analytics database built on Apache Spark and Apache Geode; the repository is now legacy. It is a good fit for interactive analytics over large datasets and maintaining legacy Spark-based deployments.

Is SnappyData open source?

Yes. SnappyData is open source under a custom licence. Its source code is on GitHub at TIBCOSoftware/snappydata and is written mainly in Scala.

Yes. SnappyData is open source, so the software itself is free to use under the terms of its own licence.

Can I self-host SnappyData?

Yes. SnappyData can be self-hosted on your own server or infrastructure.

What is SnappyData an alternative to?

SnappyData is an open-source alternative to Databricks and Snowflake. Other open-source alternatives to Databricks include Apache Cloudberry and Dremio OSS.

Is SnappyData actively maintained?

The most recent commit to SnappyData was on 21 November 2022, and the latest release is v1.3.1, published on 12 June 2022. The project has 1k stars on GitHub.

SnappyData: open-source alternative to Databricks, Snowflake

About SnappyData

SnappyData is a distributed, memory-optimized analytics database that combines an in-memory hybrid database with Apache Spark. In one cluster it provides analytic query processing, mutable data with transactions, access to many big data sources and stream processing. TIBCO also marketed it as ComputeDB.

A typical use is interactive analytics over large datasets with little pre-processing, avoiding the need to pre-aggregate data or build cubes for ad hoc visual analytics. It manages data in memory, generates code with vectorization optimizations and makes use of multi-core CPUs to keep response times low. The README stresses it is not a data warehouse replacement but a compute and caching cluster that augments warehouses and data lakes.

The repository is provided for legacy users and informational purposes only: TIBCO states it provides no updates, including security updates, and that the code may contain vulnerabilities. The TIBCO code is under the Apache License 2.0, although the repository metadata lists the license as Other. Evaluate it carefully before any new deployment.

Key features

In-memory distributed analytics database
Built on Apache Spark and Apache Geode
Transactions and mutable data
Stream processing in the same cluster
Access to many big data sources
Ad hoc analytics without pre-aggregation

Good fit for

→Interactive analytics over large datasets
→Maintaining legacy Spark-based deployments

Built with: Scala
Tags: analytics; in-memory-database; apache-spark; apache-geode; streaming; big-data; scala; legacy

SnappyData: questions and answers

What is SnappyData used for?: SnappyData, also called TIBCO ComputeDB, is an in-memory analytics database built on Apache Spark and Apache Geode; the repository is now legacy. It is a good fit for interactive analytics over large datasets and maintaining legacy Spark-based deployments.
Is SnappyData open source?: Yes. SnappyData is open source under a custom licence. Its source code is on GitHub at TIBCOSoftware/snappydata and is written mainly in Scala.
Is SnappyData free?: Yes. SnappyData is open source, so the software itself is free to use under the terms of its own licence.
Can I self-host SnappyData?: Yes. SnappyData can be self-hosted on your own server or infrastructure.
What is SnappyData an alternative to?: SnappyData is an open-source alternative to Databricks and Snowflake. Other open-source alternatives to Databricks include Apache Cloudberry and Dremio OSS.
Is SnappyData actively maintained?: The most recent commit to SnappyData was on 21 November 2022, and the latest release is v1.3.1, published on 12 June 2022. The project has 1k stars on GitHub.