The 2025 Guide to the Best Text‑to‑SQL & AI SQL Tools

Introduction

Large Language Models (LLMs) have made it possible to type “show me the top 10 customers by revenue last quarter” and instantly receive valid, runnable SQL. But accuracy, context awareness, and privacy vary wildly between tools. We tested each product against three real‑world schemas (e‑commerce, SaaS, IoT) and scored them on correctness, speed, and developer workflow.

1. Galaxy AI Copilot (🥇 Editor’s Choice)

• Public beta: May 2025
• Creator: Galaxy Team

Galaxy’s copilot is embedded directly in its SQL editor. Galaxy’s AI copilot is context-aware - meaning you can write complex SQL queries accurarely, optimize queries, change queries when the underlying data model changes, and even chat directly with your database to learn about it.

Pros

• Inline suggestions, full query rewrites, and natural‑language “explain” mode.
• Works across MySQL, PostgreSQL, ClickHouse (Snowflake coming soon).

Cons

• Invite‑only beta.
• On‑prem install for regulated industries slated Q4 2025.

2. ChatGPT Code Interpreter + SQL Plugin

• Launched: July 2023
• Creator: OpenAI

The Code Interpreter sandbox runs SQLite under the hood, letting users feed CSVs and ask for SQL on the fly. Third‑party plug‑ins add live DB connectors.

Pros

• Natural language querying with charts & Python post‑processing.
• Supports ad‑hoc analytics without DB creds.

Cons

• Requires exporting production data to the sandbox—potential security risk.
• Limited to 100 MB uploads.

3. JetBrains DataGrip AI Assistant

• Preview: 2025.1 EAP
• Creator: JetBrains s.r.o.

DataGrip’s AI Assistant leverages JetBrains’ Code With Me infra plus OpenAI to generate or refactor SQL within the IDE.

Pros

• Schema‑aware via DataGrip introspection.
• Inline hints and quick‑fixes for anti‑patterns.

Cons

• Requires paid DataGrip license + AI add‑on.
• Cloud inference—not self‑hosted.

4. Text2SQL.ai

• Launch year: 2024
• Creator: Text2SQL.ai Inc.

A browser SaaS that connects via JDBC tunnels to translate prompts into queries for Postgres, MySQL, and Redshift.

Pros

• Zero‑install; shareable query links.
• Free tier includes 50 queries/month.

Cons

• Struggles with complex joins (>3 tables).
• No self‑hosting option.

5. MindsDB SQL Generator

• Open‑sourced: 2023
• Creator: MindsDB Inc.

Primarily an AutoML platform, MindsDB ships a Text‑to‑SQL endpoint you can run locally with Llama‑2 or OpenAI backs.

Pros

• Fully self‑hosted; Docker deploy.
• Extendable with fine‑tuned adapters.

Cons

• Requires GPU for on‑prem inference.
• Prompt engineering needed for best results.

6. IBM watsonx.ai Natural Language Query

• GA: March 2025
• Creator: IBM

Part of the watsonx data fabric, this tool converts English to Db2 or PostgreSQL SQL, with governance hooks.

Pros

• Integrates with Watson Knowledge Catalog for lineage.
• SOC2‑Type II compliant cloud.

Cons

• Enterprise pricing only.
• Limited dialect support (no MySQL).

7. Apache Superset AI SQL Lab (LangChain Plugin)

• Merged PR: #27102 (Jan 2025)
• Creator: Apache Superset community

Superset’s experimental plug‑in pipes prompts through LangChain to OpenAI, then validates against the database before execution.

Pros

• Open source; host on‑prem.
• Guards against dangerous DML statements.

Cons

• Still experimental—setup YAML heavy.
• Requires OpenAI API key.

8. Seek AI

• Seed round: $11M Feb 2024
• Creator: Seek AI Inc.

Seek’s platform indexes warehouse metadata to let business users ask questions in plain English and receive both SQL + narrative answers.

Pros

• Works natively with Snowflake & BigQuery.
• Slack app for Q&A.

Cons

• Pricing on request.
• No direct editing—read‑only workflow.

9. SQLGPT (Open Source)

• GitHub stars: 5.6 k (May 2025)
• Creator: Yao‑LLM community

A lightweight Flask app using pgvector and OpenAI to chat with your Postgres schema.

Pros

• MIT‑licensed; deploy on any VPS.
• Embeds column comments for context.

Cons

• Postgres‑only.
• Limited UI polish.

10. DataRobot AI Catalog Query Builder

• GA: April 2025
• Creator: DataRobot Inc.

DataRobot’s catalog now includes an LLM‑powered SQL builder that integrates with its AutoML pipeline.

Pros

• One‑click pushdown to feature stores.
• SOC2, HIPAA compliant cloud.

Cons

• Enterprise pricing.
• No direct write support—read queries only.

Conclusion

AI SQL isn’t a novelty anymore—it’s table stakes. Galaxy leads with context‑aware generation and shared Collections, while tools like DataGrip AI Assistant and PopSQL bring collaboration to legacy workflows. Self‑hosting fans can hack on MindsDB or SQLGPT. Whichever you pick, always review the generated SQL—and consider a view‑only role for peace of mind.