Open source big-data projects
Every project in the registry tagged big-data, ranked by real GitHub adoption.
Lightning-fast analytics for massive datasets
Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
A distributed, fast open-source graph database featuring horizontal scalability and high availability
The world's fastest open query engine for sub-second analytics both on and off the data lakehouse. With the flexibility to support nearly any scenario, StarRock
Lightning-fast search for massive datasets
An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
Seamless multi-primary syncing database with an intuitive HTTP/JSON API, designed for reliability
Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more.
Time-series database built for industrial IoT workloads
Scalable SQL database for real-time analytics
🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba | 一站式图计算系统
A graph database that supports more than 100+ billion data, high performance and scalability (Include OLTP Engine & REST-API & Backends)
An easy to use, self-service open BI reporting and BI dashboard platform.
Open-source BI for engineers
Distributed Big Data Orchestration Service
:bar_chart: :clipboard: Dashboards using YAML or JSON files
Unlock Data's Potential with Open Source Power
Multi-Modal Database replacing MongoDB, Neo4J, and Elastic with 1 faster ACID solution, with NetworkX and Pandas interfaces, and bindings for C 99, C++ 17, Pyth
A simplified, lightweight ETL Framework based on Apache Spark
Related tags
Frequently asked questions
How many open source big-data projects are there?
This registry tracks 19 projects tagged big-data, with 152,447 GitHub stars between them. The most-adopted is ClickHouse at 50,719 stars.
Are these big-data projects free to use?
Yes — 19 of the 19 carry an explicit open-source licence across 2 distinct licences, so there is no licence fee. Where a project also sells a hosted or enterprise version, the self-hosted path remains free.
Which big-data project should I choose?
The list above is ranked by GitHub stars, but stars measure attention rather than fit. Check three things on each card: the licence (permissive versus copyleft), the language it is written in, and the last-push date — a high-star project that has not been pushed in a year is a liability.
Are these big-data projects still maintained?
18 of the 19 were pushed in the last 90 days, and every card shows its exact last-push date so you can see the rest. Sort your shortlist by that date before committing to a migration.