oceanbase/seekdb
The AI-Native Search Database. Best for agent storage, it unifies vector, text, structured, and semi-structured data into a single engine. This all-in-one database makes agents smarter, easier to run, and more stable. observed · 2026-08-28
Health v2 · maintenance only
74/100
- Activity 99
- Release rhythm 73
- Longevity 22
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: 42.5
- age_days: 316
- days_rel: 100
- days_push: 7
- n_releases_24m: 5
Adoption not part of the score
2882 stars · 319 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
seekdb is an AI-native search database from OceanBase that unifies relational, vector, full-text, JSON, and GIS data in a single MySQL-compatible engine. It supports embedded and client/server deployment, hybrid search (vector + keyword + relational in one SQL query), and in-database AI functions like embedding, reranking, and LLM completion.
Use cases
- store and search embeddings for RAG applications
- hybrid vector and keyword search in one query
- embedded vector database for Python AI agents
- agent memory and state storage
- MySQL-compatible database with vector search
- build knowledge bases with automatic embeddings
- run in-database LLM inference and reranking via SQL
When to choose
- you need vector, full-text, and relational search unified in one engine
- you want an embedded, lightweight vector DB for prototyping or agent apps
- you prefer SQL and MySQL ecosystem compatibility over a separate vector store
- you're building RAG pipelines with LangChain, LlamaIndex, or Dify
When to avoid
- you need a distributed, horizontally scalable database (seekdb doesn't support distributed mode)
- you require in-place upgrades between minor versions, which are currently unsupported
- you need embedded mode on Windows, which is not yet supported
- you need battle-tested production stability at very large scale
Facets
application · maturity active
vector-database search-engine database rag llm-inference databases artificial-intelligence developer-tools windows python cpp rust self-hosted hybrid-search hnsw full-text-search mysql-compatible embedded-database agent-memory copy-on-write langchain llamaindex sql search ai-agents retrieval-augmented-generation linux macos docker
10 sources
- readme: https://github.com/oceanbase/seekdb · fetched 2026-08-28 · 602347972274
- homepage: https://seekdb.ai · fetched 2026-08-29 · bf246179e06d
- site_page: https://docs.seekdb.ai/docs · fetched 2026-08-29 · c3a895b77467
- site_page: https://docs.seekdb.ai/seekdb/changelog · fetched 2026-08-29 · 51cc8b6684de
- site_page: https://docs.seekdb.ai/docs/using-seekdb-in-python-sdk · fetched 2026-08-29 · dc3e1c1f0004
- site_page: https://docs.seekdb.ai/docs/experience-hybrid-search · fetched 2026-08-29 · a7fe11c706ef
- site_page: https://docs.seekdb.ai/docs/experience-vector-search · fetched 2026-08-29 · fb38aa909fa0
- site_page: https://docs.seekdb.ai/docs/experience-ai-function · fetched 2026-08-29 · 0761a0401318
- site_page: https://docs.seekdb.ai/docs/api-overview · fetched 2026-08-29 · 7e2de3c787fd
- site_page: https://docs.seekdb.ai/docs/pyseekdb-sdk-get-started · fetched 2026-08-29 · 690217cdb636
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| oceanbase/seekdb | main | 74 |
For agents
markdown · JSON · MCP: product_card(name="oceanbase/seekdb")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem