> For the complete documentation index, see [llms.txt](https://mariadb.com/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://mariadb.com/docs/server/reference/sql-structure/vectors/vector-framework-integrations.md).
# Vector Framework Integrations
WEBINAR
The Next Generation of MariaDB: Powered by Vector Search
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[Vectors](/docs/server/reference/sql-structure/vectors.md) are available from [MariaDB Community Server 11.7](/docs/release-notes/community-server/old-releases/11.7/what-is-mariadb-117.md) and from [MariaDB Enterprise Server 11.4.5-3](/docs/release-notes/enterprise-server/11.4/11.4.5-3.md).
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MariaDB Vector has integrations in several frameworks. For a general overview of MariaDB Vector — feature summary, benchmarks, tutorials, and demos — see the [MariaDB Vector project page](https://mariadb.org/projects/mariadb-vector/).
## AI Framework Integrations
* [LangChain, MariaDB Vector Store](https://docs.langchain.com/oss/python/integrations/vectorstores/mariadb) - Python ([PyPI package](https://pypi.org/project/langchain-mariadb/))
* [LangChain4j, MariaDB Embedding Store](https://docs.langchain4j.dev/integrations/embedding-stores/mariadb/) - Java
* [LlamaIndex, MariaDB Vector Store](https://developers.llamaindex.ai/python/framework-api-reference/storage/vector_store/mariadb/) - Python
* [MCP (Model Context Protocol), MariaDB MCP server](https://github.com/mariadb/mcp) - Python
* [Spring AI, MariaDB Vector Store](https://docs.spring.io/spring-ai/reference/api/vectordbs/mariadb.html) - Java
* [VectorDBBench](https://github.com/zilliztech/VectorDBBench) - benchmarking for vector databases
## Web Framework and ORM Integrations
* [Laravel, vector columns and vector indexes in the schema builder](https://laravel.com/docs/13.x/migrations#column-method-vector) - PHP, since Laravel 13; `$table->vectorIndex('embedding')` compiles to a MariaDB `VECTOR INDEX` with `M=6 DISTANCE=cosine` ([laravel/framework#60334](https://github.com/laravel/framework/pull/60334))
* [laravel-mariadb-vector, vector casts and similarity search for Eloquent models](https://packagist.org/packages/devilsberg/laravel-mariadb-vector) - PHP, community package
* [TypeORM, MariaDB vector columns](https://typeorm.io/docs/drivers/mysql/) - TypeScript/Node.js, since TypeORM 0.3.28
* [Hibernate ORM, MariaDB vector type](https://hibernate.atlassian.net/browse/HHH-18900) - Java, since Hibernate ORM 7.0
For a worked example of picking an embedding model for MariaDB Vector in a Laravel application, see [MariaDB Vector in Laravel: insights on choosing an embedding model](https://mariadb.org/mariadb-vector-in-laravel-insights-on-choosing-an-embedding-model/).
## Potential Future Vector or AI Integrations
* [AutoGen](https://github.com/microsoft/autogen) - Agent to agent, Python
* [DB-GPT](https://github.com/eosphoros-ai/DB-GPT) - private LLM, vector search and text2sql, see [integration docs](http://docs.dbgpt.cn/docs/installation), Python
* [Feast](https://github.com/feast-dev/feast) - machine learning (not GenAI), Python
* [Firebase Studio template for MariaDB Vector](https://firebase.uservoice.com/forums/948424-general/suggestions/49702310-mariadb-vector) - visit link to vote for suggestion
* [LangGraph](https://github.com/langchain-ai/langgraph) - Agentic workflow, Python
* [MindSQL](https://github.com/Mindinventory/MindSQL) - Text-to-SQL RAG Library simplifying database interactions, Python
* [Open WebUI](https://github.com/open-webui/open-webui) - AI Interface, Python & Javascript
* [Vanna AI](https://github.com/vanna-ai/vanna) - Vector search and text2sql, Python
For the full, continuously updated catalog of AI frameworks, platforms, and tools that work with MariaDB, see the [AI & Application Development category of the MariaDB Ecosystem Hub](https://ecohub.mariadb.org/ai-application-development).
*This page is licensed: CC BY-SA / Gnu FDL*
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