# matrixorigin/matrixone

AI-native HTAP database with Git-for-Data and built-in vector search, serving as the data and memory backbone for intelligent agents and applications.

Repository: https://github.com/matrixorigin/matrixone
Canonical: https://ross.abutalabs.com/products/matrixone
Homepage: https://docs.matrixorigin.cn/mo/en/
Language: Go
License: Apache-2.0
License Family: permissive
Topics: distributed-database, distributed-systems, cloud-native, olap, htap, one-size-fits-all, hyperconverged, sql, go, database, ai-native, fulltext-support, git-for-data, mysql-compatible, vector-database, agents, memory
Last push: 2026-08-26T18:24:42+00:00

## Health v2 (maintenance only)
Score: 99/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 99, longevity 100
- inputs: {"age_days": 2022, "days_push": 7, "days_rel": 7, "gap_med": 6.0, "n_releases_24m": 53}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1881, forks 309 (observed 2026-08-28T04:05:48.686840+00:00)

## What it is
MatrixOne is a cloud-native, distributed HTAP SQL database written in Go that is MySQL-compatible and includes built-in vector search and full-text search. It uniquely offers Git-style version control for data (Git-for-Data), positioning itself as a data and memory backbone for AI agents and applications.

## Use cases
- run a mysql-compatible distributed sql database
- store and query vector embeddings for ai agents
- combine transactional and analytical workloads in one database
- version and branch data like git
- build rag applications with built-in vector and fulltext search
- self-host a cloud-native htap database on kubernetes

## When to choose
- you need one database for both OLTP and OLAP workloads
- you want vector search alongside relational SQL without a separate vector database
- you need MySQL wire compatibility in a distributed, cloud-native deployment
- you want data versioning/branching capabilities

## When to avoid
- you need a battle-tested database with a large production track record
- you only need a simple single-node relational database
- you depend on advanced MySQL-specific features not fully implemented
- your stack is tightly bound to PostgreSQL extensions

## Facets
- artifact type: service
- maturity: active
- function: database, vector-database, search-engine
- domain: databases, large-language-models, cloud-computing, microservices
- platform: go, self-hosted, cloud
- tags: htap, mysql-compatible, git-for-data, ai-native, olap, distributed-sql, vector-search, fulltext-search, sql, ai-agents, linux, macos, docker, kubernetes

## Member repositories
- matrixorigin/matrixone (main) score 99

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:48.686840+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:13:58.388546+00:00, confidence not recorded.
  - readme: https://github.com/matrixorigin/matrixone (fetched 2026-08-28T04:05:48.686840+00:00, sha 5a72410bf9eb)
  - homepage: https://docs.matrixorigin.cn/mo/en/ (fetched 2026-08-29T10:53:03.475630+00:00, sha 491a453936ef)
- Data as of 2026-08-30T08:39:29.467469+00:00.