MindsDB
MindsDB is an open-source artificial intelligence software platform that enables organizations to analyze both structured and unstructured data without requiring it to be moved into a separate storage system. It connects to existing databases, business applications, and document-based sources, allowing information to be queried directly from its current location.
History
MindsDB was founded in 2017 by Jorge Torres and Adam Carrigan in Berkeley, California. The first open-source release in 2018 introduced basic machine-learning functions that operated inside traditional databases. From 2019 to 2024, the project expanded into a broader system for accessing distributed enterprise data. Independent technology publications referenced MindsDB during this period in the context of AI infrastructure and data engineering tools.Between 2024 and 2025, MindsDB added features for working with large language models and retrieval-augmented generation, positioning the platform as an open-source engine for running AI queries across different data systems.
Overview
MindsDB has formed strategic partnerships with leading companies such as Snowflake, SingleStore, DataStax, and NVIDIA. As of September 2024, the platform supports over 200 integrations, including popular large language models like OpenAI, Anthropic, and Mistral, as well as data platforms such as MySQL, PostgreSQL, Snowflake, and MongoDB. MindsDB also integrates with a wide range of applications, including Salesforce, HubSpot, X, and many others.Technology
Federated data access
MindsDB offers a federated query engine – a system that allows SQL queries to run across multiple databases, business applications, and document-based sources without combining the data into one central repository. This makes it possible to analyze live operational information while it remains in its original location.Document and file search
MindsDB provides tools for managing and searching unstructured content such as documents and text fields:- vector search – a method for finding similar content by comparing numerical representations of text
- metadata filtering – narrowing search results by attributes such as date or category
AI data agents