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SQL Optima
Automated SQL query analyzer and performance optimizer
An automated SQL performance analyzer, schema linter, and query execution optimizer built for GitHub Actions. Parses raw SQL code or schema files, identifies structural anti-patterns, connects to ephemeral database containers (PostgreSQL / MySQL / MariaDB / SQL Server) or an in-memory SQLite engine, and evaluates query execution plans (EXPLAIN / SHOWPLAN) to flag sequential scans, disk sorts, and full table scans. BigQuery and Snowflake are supported for static dialect linting only.
Hey Product Hunt community! 👋
I built SQL Optima as a GitHub Action to automate SQL performance reviews directly inside CI/CD workflows.
Instead of relying on AI tools that can sometimes hallucinate, SQL Optima combines AST syntax parsing with real EXPLAIN execution plans on your database. It catches full table scans, missing indexes, and anti-patterns right in your Pull Requests before they hit production.
It's 100% open source, and I’d love to get your feedback, hear your thoughts, or receive contributions for new analyzer rules. Thanks for checking it out! 🚀
About SQL Optima on Product Hunt
“Automated SQL query analyzer and performance optimizer”
SQL Optima was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #64 on the daily leaderboard. An automated SQL performance analyzer, schema linter, and query execution optimizer built for GitHub Actions. Parses raw SQL code or schema files, identifies structural anti-patterns, connects to ephemeral database containers (PostgreSQL / MySQL / MariaDB / SQL Server) or an in-memory SQLite engine, and evaluates query execution plans (EXPLAIN / SHOWPLAN) to flag sequential scans, disk sorts, and full table scans. BigQuery and Snowflake are supported for static dialect linting only.
On the analytics side, SQL Optima competes within Open Source, GitHub and Database — topics that collectively have 112.5k followers on Product Hunt. The dashboard above tracks how SQL Optima performed against the three products that launched closest to it on the same day.
Who hunted SQL Optima?
SQL Optima was hunted by Fidel Alejandro Fernandez Arias. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of SQL Optima including community comment highlights and product details, visit the product overview.
Fidel Alejandro Fernandez Arias