StarRocks/starrocks
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, StarRocks provides best-in-class performance for multi-dimensional analytics, real-time analytics, and ad-hoc queries. A Linux Foundation project. observed · 2026-08-28
Health v2 · maintenance only
95/100
- Activity 99
- Release rhythm 87
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 7
- age_days: 1825
- days_rel: 7
- days_push: 7
- n_releases_24m: 74
Adoption not part of the score
12043 stars · 2544 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
StarRocks is a high-performance distributed OLAP database and query engine built on an MPP architecture with a fully vectorized execution engine and columnar storage. It supports sub-second analytics on internal tables and directly on data lakehouse formats like Apache Iceberg, Delta Lake, and Hudi, with MySQL protocol compatibility.
Use cases
- run sub-second ad-hoc SQL queries on large datasets
- query Apache Iceberg, Delta Lake, or Hudi tables without data migration
- power real-time dashboards and BI tools with high concurrency
- ingest streaming CDC data from Kafka and Flink for fresh analytics
- serve low-latency analytics to AI agents
- perform multi-dimensional and multi-table join analytics at scale
When to choose
- you need sub-second query latency for complex analytical SQL at high concurrency
- you want to analyze data lakehouse tables directly without ETL or denormalization
- you need real-time updates and deletes with fast query performance
- you want MySQL protocol compatibility with existing BI tools
When to avoid
- you need a simple transactional (OLTP) database for application CRUD workloads
- you cannot operate a distributed cluster and only need single-node embedded analytics
- your workload is primarily document or key-value storage rather than analytical SQL
Facets
service · maturity active
database search-engine analytics streaming etl databases big-data analytics cloud self-hosted olap mpp sql lakehouse data-warehouse iceberg delta-lake hudi vectorized-execution mysql-protocol columnar-storage real-time-analytics data-engineering real-time linux docker kubernetes
6 sources
- readme: https://github.com/StarRocks/starrocks · fetched 2026-08-28 · 1f4d3deeb856
- homepage: https://starrocks.io · fetched 2026-08-29 · f4e279a5ed85
- site_page: https://docs.starrocks.io · fetched 2026-08-29 · 44136fa355b3
- site_page: https://docs.starrocks.io/docs/quick_start · fetched 2026-08-29 · ba5a12ff46b4
- site_page: https://docs.starrocks.io/docs/introduction/StarRocks_intro · fetched 2026-08-29 · 79a1ffbffbba
- site_page: https://www.starrocks.io/feature/index.html · fetched 2026-08-29 · 72ae8d8296e0
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| StarRocks/starrocks | main | 95 |
For agents
markdown · JSON · MCP: product_card(name="StarRocks/starrocks")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem