Chion vs Natural Language SQL

Chion turns plain-English questions about PostgreSQL into code-validated, read-only SQL and interactive D3 charts, displaying the SQL beneath each chart. It connects directly to PostgreSQL without ETL or a warehouse copy, supporting Amazon RDS, Azure Database for PostgreSQL, Google Cloud SQL, Neon, Supabase, and self-hosted PostgreSQL. Validators reject statements that are not read-only SELECT queries before database execution. Results are limited to 1,000 rows or 12,000 cells. Eight built-in chart types include line, area, bar, and animated bar-race formats. Saved queries can become portable SQL skill files for Claude Code and Codex. Chion runs in the cloud through the web. Starter costs $29/seat/mo, Pro $99/seat/mo, and Max $299/seat/mo, each with a seven-day trial; Enterprise uses custom per-team pricing. Credentials are encrypted in an AES-256-GCM vault, while Chion says it is not SOC 2 certified and does not support HIPAA workloads.

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.