20 Most Popular Open-Source Database & Data Processing Tools
The most-starred open-source databases, data warehouses and stream-processing engines — SQL, NoSQL, time-series, graph and vector — with GitHub links and star counts.
By The DevFixPro Editorial Team · independent editorial research project
Star counts retrieved from the GitHub API on 2026-08-17. Open-source projects grow daily, so treat the numbers as a snapshot — always check the linked repository for the latest figures, license, and activity.
Data lives in many shapes. The 20 open-source databases and data-processing engines below are ranked by GitHub stars (fetched 2026-08-17) — relational, document, key-value, time-series, graph, columnar and streaming. Each links to its GitHub repository.
Match the engine to the workload: Postgres/MySQL for transactions, Redis for cache, ClickHouse/DuckDB for analytics, InfluxDB for time-series, Neo4j for graphs, Kafka/Spark/Flink for streaming and batch.