This post is maintained by Bytebase, an open-source database DevSecOps tool. We update the post gradually.
| Update History | Comment |
|---|---|
| 2024/09/11 | Initial version. |
| 2025/05/27 | 2025 Update. |
If you work with databases, SQL AI tools can significantly improve your productivity and efficiency. They help generate SQL commands automatically from natural language input and optimize query performance as functional and starter-friendly tool.
Here we gathered some of the most popular SQL AI tools (Text2SQL) on the market in 2024.
DataGrip
JetBrains introduces an AI Assistant to its flagship SQL client DataGrip.
The DataGrip AI assistants can:
- Request queries and information using a natural language.
- Explain complex SQL such as stored procedure.
- Optimize schema and SQL.
- Compare DDL of two database objects.
- Fix SQL mistakes.
- Format and rewrite SQL.
SQL Chat
SQL Chat is a chat-based SQL client, which uses natural language to communicate with the database to implement operations such as query, modification, addition, and deletion of the database. Instead of navigating across many UI controls, SQL chat applies a much more intuitive chat-based interface, bringing more flexible and comfortable user experience.
SQL Chat supports the following databases and will add more over time:
- MySQL
- PostgreSQL
- MSSQL
- TiDB Cloud
Vanna.ai
Vanna.ai is a personalized AI SQL agent that transforms natural language questions into actionable database insights. The platform offers multiple deployment options to suit different organizational needs:
- Vanna Cloud: Enterprise-ready platform with zero setup, trained on your specific data environment and industry context
- Vanna Enterprise: On-premises deployment within your own infrastructure for complete data sovereignty
- Vanna API: Integration capabilities for embedding AI-powered database interactions into existing applications
- Open-Source Foundation: Maximum flexibility for developers who want to build custom solutions
The platform supports major databases including Snowflake, BigQuery, Postgres and MySQL, with easy connector creation for others. Vanna can be deployed through various frontends—from Jupyter notebooks to Slack bots, web apps, and Streamlit interfaces.
SQLAI.ai
SQLAI.ai is divided into several SQL generators, each serving specific purposes:
- Explain SQL Queries: Offers explanations with summaries, output visualizations, and detailed query breakdowns.
- Format SQL Query: Formats SQL queries for improved readability and reduced error-proneness.
- Analyze Your Data: Allows you to upload CSV data and ask AI questions.
- Generate SQL Query, Fix SQL Queries, Optimize SQL Query, etc.
In addition to the core generators, SQLAI.ai includes tools to facilitate your work. The available tools vary depending on the generator.
Outerbase
Outerbase has been acquired by Cloudflare in 2025
Outerbase impresses users at first sight with its strong-sense-of-tech and comics-style interface.
It supports a variety of SQL or NoSQL databases.
Outerbase develops its AI agent EZQL to understand your natural language prompts.
Honorable mention: Postgres.new
Postgres.new is an WASM-based in-browser PostgreSQL sandbox with AI assistance. It allows users to operate with PostgreSQL directly in a web browser, without having to install or set up the database locally.
Postgres.new is currently in early alpha with limited functionality. It may have limitations compared to a full native PostgreSQL installation.
Techniques and Benchmarks
Cloud hyperscalers are increasingly integrating Text-to-SQL capabilities across their database offerings. Google Cloud, for example, has rolled out this feature to BigQuery, Cloud SQL, and AlloyDB, and recently published guidance on effective AI prompting techniques for SQL generation. Meanwhile, the research community has developed evaluation frameworks like BIRD-Bench to measure Text-to-SQL accuracy.
Text-to-SQL tools improve efficiency, make it easier to interact with databases. Although they also use state-of-the-art LLM models, the results may sometimes be inaccurate. If you want to use them in production, make sure to double-check before you hit RUN.
