Is deepsql open source?

Yes, licensed under Apache-2.0.

deepsql

Active·★ 25·Apache-2.0·Updated 2026-09-10

★ Hidden Gem★ Trending

DeepSQL is an AI-powered database agent for PostgreSQL and MySQL, allowing users to interact with their databases, generate queries, analyze performance, and manage schema using plain English. It is model-agnostic, enabling integration with various LLM providers like OpenAI, Azure OpenAI, or self-hosted models, while keeping all sensitive data and operations within the user's controlled environment.

deepsql is currently grouped under Data Processing, which makes it easier to evaluate through workflow fit instead of isolated features alone. Based on the available data, it leans most heavily toward Answer BI questions in plain English by generating, validating, and executing read-only SQL. and Database administrators or data engineers seeking AI assistance for routine tasks and performance tuning.. The listed license is Apache-2.0, which is useful when adoption constraints matter. It also shows measurable community traction with 25 GitHub stars.

#Database Agent#PostgreSQL#MySQL#SQL Generation#LLM Integration#Database Performance#Schema Management#Data Analytics

Features

01Answer BI questions in plain English by generating, validating, and executing read-only SQL.

02Identify and fix slow queries by analyzing logs and flagging regressions against baselines.

03Provide index recommendations and apply them concurrently on PostgreSQL without table locks.

04Monitor and track schema changes to detect drift before it impacts queries or dashboards.

05Establish a 'brain' that understands business metrics, rules, and conventions for consistent query generation and recommendations.

Why choose it

+Answer BI questions in plain English by generating, validating, and executing read-only SQL.

+Database administrators or data engineers seeking AI assistance for routine tasks and performance tuning.

+Covers 4 supported environments or platforms, which is helpful for broader deployment needs.

+Ships with a public repository and a Apache-2.0 license, which makes adoption and review easier.

Trade-offs

!There are at least 8 related tools in the same category, so the best choice is easier to make after side-by-side comparison.

Compatibility

PostgreSQL

Database

Verified via docs

MySQL

Database

Verified via docs

Docker Engine

Runtime

Verified via docs

OpenAI API Compatible LLMs

LLM Provider

Verified via docs

Quick start

$ git clone https://github.com/DeepSQLAI/deepsql.git

$ cd deepsql

$ cp .env.example .env

$ ./scripts/self-host/install.sh

Use cases

↳Database administrators or data engineers seeking AI assistance for routine tasks and performance tuning.

↳Business analysts or stakeholders needing to get insights from databases using natural language without writing SQL.

↳Teams aiming to automate the generation of dashboards and reports based on business context.

↳Organizations looking for a secure way to integrate LLMs with their databases, keeping data within their own infrastructure.

↳Developers wanting to enhance their coding agents with direct, safe database interaction capabilities.

How it compares

≈deepsql sits in the Data Processing category, so it makes more sense to evaluate it alongside tools like mirascope instead of in isolation.

≈If your main need is closer to "Database administrators or data engineers seeking AI assistance for routine tasks and performance tuning.", that use case is a better lens for comparison than broad feature checklists alone.

≈deepsql uses a Apache-2.0 license, and community traction are both easier to judge in category context.

Features

Why choose it

Trade-offs

Compatibility

Quick start

Use cases

How it compares

Alternatives

Related searches

Comments

Features

Why choose it

Trade-offs

Compatibility

Quick start

Use cases

How it compares

Alternatives

Related searches

Comments