Skip to content

docs: update text-to-sql blog to 2026 #1008

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
tianzhou merged 6 commits into from
Feb 5, 2026
+38 −16
Merged

docs: update text-to-sql blog to 2026 #1008

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
fc2b4bf
update text-to-sql blog to 2026
adela-bytebase Feb 3, 2026
b9eca9c
Apply suggestion from @Copilot
tianzhou Feb 5, 2026
b295b8e
Apply suggestion from @Copilot
tianzhou Feb 5, 2026
7fb67da
Apply suggestion from @Copilot
tianzhou Feb 5, 2026
f58c8ea
Apply suggestion from @Copilot
tianzhou Feb 5, 2026
6d9a56f
Apply suggestion from @tianzhou
tianzhou Feb 5, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
54 changes: 38 additions & 16 deletions content/blog/top-text-to-sql-query-tools.md
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,10 +1,10 @@
---
title: Top 5 Text-to-SQL Query Tools in 2025
title: Top 5 Text-to-SQL Query Tools in 2026
author: Ayra
updated_at: 2025/12/04 12:00:00
feature_image: /content/blog/top-text-to-sql-query-tools/banner.webp
updated_at: 2026/02/03 12:00:00
feature_image: /content/blog/top-text-to-sql-query-tools/cover.webp
tags: Industry
description: 'An overview to the most popular text-to-SQL AI tools in 2025, including DataGrip, TablePlus, SQL Chat, Vanna.ai, SQLAI.ai, Postgres.new, and DBHub MCP server. Compare features and capabilities to find the best SQL AI assistant for your workflow.'
description: 'An overview of the most popular text-to-SQL AI tools in 2026, including DataGrip, TablePlus, SQL Chat, Vanna.ai, SQLAI.ai, Postgres.new, and DBHub MCP server. Compare features and capabilities to find the best SQL AI assistant for your workflow.'
---

<HintBlock type="info">
Expand All @@ -18,6 +18,7 @@ This post is maintained by Bytebase, an open-source database DevSecOps tool. We
| 2024/09/11 | Initial version. |
| 2025/05/27 | 2025 Update. |
| 2025/12/04 | Add TablePlus and DBHub. Remove Outerbase (acquired by Cloudflare). |
| 2026/02/03 | 2026 Update. Update DataGrip and Vanna.ai with major new features. |

This is a series articles about SQL Clients / SQL Editors:

Expand All @@ -28,23 +29,31 @@ This is a series articles about SQL Clients / SQL Editors:

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.
Here we gathered some of the most popular SQL AI tools (Text2SQL) on the market in 2026.

## DataGrip

JetBrains introduces an AI Assistant to its flagship SQL client [DataGrip](https://www.jetbrains.com/datagrip/).

![](/content/blog/top-text-to-sql-query-tools/datagrip.webp)

The DataGrip AI assistants can:
The DataGrip AI Assistant can:

1. Request queries and information using a natural language.
1. Explain complex SQL such as stored procedure.
1. Request queries and information using natural language.
1. Explain complex SQL such as stored procedures.
1. Optimize schema and SQL.
1. Compare DDL of two database objects.
1. Fix SQL mistakes.
1. Format and rewrite SQL.

During 2025, JetBrains significantly enhanced the AI Assistant:

- **Schema and object context**: Attach specific database objects (tables, views) to AI chat for more precise responses, not just the whole schema.
- **Execution plan analysis**: AI can explain query execution plans and suggest optimizations for better performance.
- **Cloud-based code completion**: Leverages cloud resources for more precise autocomplete, including single lines, code blocks, and entire scripts.
- **Cloud database integration**: Connect directly to AWS, Azure, and Google Cloud accounts to browse and connect to databases.
- **Free tier and local models**: A free tier offers unlimited local completions, and you can connect OpenAI-compatible local endpoints (Ollama, LM Studio) for offline use.

## TablePlus

[TablePlus](https://tableplus.com/) is considered by many as the best SQL client on Mac. It's a modern, native database management tool that supports multiple databases. It has integrated text-to-SQL AI capabilities to help developers generate queries from natural language.
Expand Down Expand Up @@ -72,14 +81,17 @@ SQL Chat supports the following databases and will add more over time:

![](/content/blog/top-text-to-sql-query-tools/vanna.webp)

[Vanna.ai](https://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.ai](https://vanna.ai/) is a personalized AI SQL agent that transforms natural language questions into actionable database insights. In late 2025, Vanna released **Vanna 2.0**, a complete architectural rewrite that evolved from a simple SQL generation library into a production-ready, user-aware agent framework.

- **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
Key features of Vanna 2.0:

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.
- **Agent-based architecture**: New Agent-based API replacing the legacy VannaBase class methods, with better support for agentic models like Claude 4.5 and GPT-5.
- **User-aware components**: Identity flows through every layer with user context automatically available in tools, SQL queries, and audit logs.
- **Enterprise security**: Row-level security with queries filtered based on user permissions, group-based access control, and comprehensive audit logging for compliance.
- **Web-first approach**: Built-in `<vanna-chat>` component and server with streaming and rich UI components.
- **NVIDIA NIM integration**: Accelerated inference using NVIDIA NIM microservices for improved performance.

The platform supports major databases including PostgreSQL, MySQL, Snowflake, BigQuery, Redshift, SQLite, Oracle, SQL Server, DuckDB, ClickHouse, and more. For LLMs, it supports OpenAI, Anthropic Claude, Google Gemini, Azure OpenAI, Ollama, and others.

## SQLAI.ai

Expand Down Expand Up @@ -112,12 +124,22 @@ Unlike standalone SQL clients, [DBHub](https://dbhub.ai) brings text-to-SQL capa

DBHub is a universal database MCP (Model Context Protocol) server that enables any MCP client such as Claude, Cursor, VS Code, and Codex to have text-to-SQL capability. It acts as a bridge between AI assistants and databases, allowing developers to use natural language to query and explore their databases directly from their development tools.

DBHub supports multiple databases including PostgreSQL, MySQL, MariaDB, SQL Server, and SQLite. Compare with other database MCP server, it comes with an admin console to view configured data sources and trace SQL requests.
As of early 2026, DBHub has over 100K downloads and 2K GitHub stars. It supports multiple databases including PostgreSQL, MySQL, MariaDB, SQL Server, and SQLite. Key features include:

- **Custom tools**: Define reusable, parameterized SQL operations in configuration files.
- **Built-in web interface**: Visual way to execute queries, run custom tools, and view request traces without requiring an MCP client.
- **Security-first design**: Read-only mode and safety controls to prevent accidental data modifications.

Compared with other database MCP servers, DBHub comes with an admin console to view configured data sources and trace SQL requests.

![](/content/blog/top-text-to-sql-query-tools/dbhub-console.webp)

## 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](https://cloud.google.com/blog/products/databases/techniques-for-improving-text-to-sql) on effective AI prompting techniques for SQL generation. Meanwhile, the research community has developed evaluation frameworks like [BIRD-Bench](https://bird-bench.github.io/) 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**.
## Security Considerations

When Anthropic introduced MCP, the Postgres server was one of the original reference implementations. Security reviews of early MCP-based database servers have shown that simply wrapping user-supplied SQL in a read-only transaction is not sufficient if the server also accepts semicolon-delimited statements, because additional statements may execute outside the intended protection. When evaluating MCP-based database tools, prioritize implementations with robust security controls such as proper SQL parsing or allow-listing, strict read-only enforcement, and clear configuration for which databases and schemas can be accessed.

Text-to-SQL tools improve efficiency and make it easier to interact with databases. Although they 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**.
Binary file removed public/content/blog/top-text-to-sql-query-tools/banner.webp
View file
Open in desktop
Binary file not shown.
Binary file added public/content/blog/top-text-to-sql-query-tools/cover.webp
View file
Open in desktop
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.