RAG и базы знаний
helix-db
An OLTP graph database with native vector and full-text search, built in Rust on object storage.
★ 6,1 тыс. звёздApache-2.0
Смотреть руководство →seekdb — проект с открытым исходным кодом из категории «RAG и базы знаний» от oceanbase (oceanbase/seekdb на GitHub). У него 3 107 звёзд на GitHub и 370 форков, он распространяется по лицензии Apache-2.0 и последний раз обновлялся на GitHub 8 октября 2026.
seekdb — the AI-native search database unifying vector, text and structured data for agents.
Decide the first concrete outcome you want from it, so you can pick the right example, template or mode instead of exploring everything at once.
Clone the repository (or install the published package) and skim its README quick start for the requirements for your platform.
Run the documented install step and set any required configuration — such as provider keys, data sources or local services — before the first run.
Execute the smallest documented example end to end, confirm the output is what you expected, then adapt it to your real data or workflow.
Vector + full-text + relational filters together, served by incremental HNSW right after writes.
FORK DATABASE lets agents experiment safely; MERGE accepts results and DROP rolls back.
Write a memory and query it in the next millisecond without P99 spikes from background rebuilds.
Works with the MySQL ecosystem and with LangChain, LlamaIndex and Dify out of the box.
Embedded library, micro-server for edge devices, single node, or the OceanBase cluster.
Positioned as the state store for agents: observations persist and are retrievable immediately.
Get the source so you can inspect, configure and run it locally.
git clone https://github.com/oceanbase/seekdb.git
cd seekdbInstall pyseekdb to use seekdb as an embedded agent store from Python.
pip install -U pyseekdbUse the one-line Linux install, Homebrew on macOS, Docker or the zero-install cloud as the README's Installation section describes.
# see README Quick Start / Installation for your platform's exact commandIt is maintained by oceanbase on GitHub (oceanbase/seekdb), where the source, issues and releases live.
Yes — it is free and open source under Apache-2.0, which permits use, modification and commercial redistribution, with licence/notice retention.
No LLM key is needed by the database; your application supplies embeddings from whichever model you choose.
Compared with a standalone vector database such as Qdrant or a plain MySQL instance, seekdb's distinguishing focus is: seekdb — the AI-native search database unifying vector, text and structured data for agents. Pick it when that focus matches your need; the alternative may suit you better if its broader or different scope is the priority.
Clone https://github.com/oceanbase/seekdb (or install its published package), follow the README quick start to install and configure it, then run the smallest documented example — the Run section on this page mirrors those steps.
An OLTP graph database with native vector and full-text search, built in Rust on object storage.
AI-native database for hybrid search across dense, sparse, and tensor vectors plus full text
Polyglot document intelligence in Rust — extract text, tables and structured data from 106 formats.
Vector similarity search inside Postgres - store embeddings next to your data
Knowhere turns documents into structured, hierarchy-native chunks ready for agents and RAG.
AI-native data platform: 60+ connectors, ETL, scheduling, and RAG search.
Другие проекты из категории «RAG и базы знаний» с наибольшим числом звёзд в каталоге LibreAI — реалистичный список альтернатив, если seekdb вам не подходит.
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Соседние проекты из категории «RAG и базы знаний» в каталоге, ближайшие по числу звёзд к seekdb — продолжайте изучать полку по обе стороны от него.
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Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.