IDERA AI SQL Query Generator vs Natural Language SQL

IDERA AI SQL Query Generator is a free web tool that turns plain-English questions into SQL drafts. Users can enter table and column names to provide schema context, then ask what they want to query. The AI model generates SQL that can be copied, edited, or regenerated before the user runs it in a separate database. The tool does not connect to or execute queries against that database. No installation is required, but a modern browser and internet connection are needed. IDERA says limits apply to keep the free tool available, without stating their values on the product page. Prompts and outputs may be logged anonymously for quality, while supplied details are not retained long term. IDERA describes the generator as a way to make SQL querying more accessible and reduce the learning curve for teams. Help is available through community forums and an email contact.

Natural Language SQL turns plain-English questions about databases into SQL, validates and runs the query, then streams back results. It connects to PostgreSQL and MySQL, including multiple databases of the same type in parallel. Hybrid retrieval combines BM25 and sentence-transformer vectors to select schema context for a question. Users can review and edit generated SQL before execution, while the interface shows progress through query stages. Results can be sorted, paginated at 50 rows per page, downloaded as CSV or JSON, or copied as tab-separated text. SELECT queries receive a default limit, explicit result counts are capped at 1,000 rows, and execution times out after 30 seconds by default. INSERT, UPDATE and DELETE are allowed by default, with warning banners; the project recommends a read-only database user to block writes. Ollama runs locally by default, keeping questions, schema and generated SQL on the user’s machine. OpenAI, Gemini and Groq are optional cloud providers and receive the question, relevant schema portion and SQL context. The project is free under GPL-3.0. Its recommended Docker setup needs Docker 20.10 or later with Compose v2 and about 10 GB of free disk space.