AI PostgreSQL Query Generator - Write & Test PostgreSQL Online

Describe what you need in plain English and get a working PostgreSQL query. Paste your table schema for exact column names, and let the AI run the query against a real test database to verify it works before you copy it.

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The Large Language Model (i.e. AI) to use for code generation.
Cost: 1 credit
Drop files or folders here or click to select. If you want to upload to the sandbox environment, please enable the Code Execution in the "Advanced Tools" below before uploading.
Try to be as specific as possible.

Paste your CREATE TABLE statements (or describe your tables) so the generated query uses your exact table and column names. With Code Execution on, the AI also uses it to build a test database and run the query. Optional, but strongly recommended
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Learn more.

PostgreSQL queries that are tested before you copy them

Most AI SQL generators hand you a query and hope it runs. This one can prove it: with Code Execution enabled, the AI spins up an ephemeral database sandbox (PostgreSQL, MySQL and SQLite are supported — MongoDB and Redis for NoSQL), creates your tables, inserts representative sample rows, runs the generated PostgreSQL query, and fixes any syntax or logic errors before showing you the result — along with the sample output it produced.

Use the schema field

Biggest accuracy boost

Paste your CREATE TABLE statements into the schema field above. The query will use your exact table and column names instead of guessed ones, and the sandbox uses the same schema to build the test database.

For the best result

  • Include the tables involved in the query, with their column types.
  • Mention the PostgreSQL version or flavor if it matters.
  • Describe the expected output columns in your prompt.
  • For optimization requests, include the current query and any indexes.

What it handles well

Beyond simple SELECTs
  • Multi-table JOINs and correlated subqueries.
  • Window functions (ranking, running totals, deduplication).
  • CTEs and recursive queries for hierarchies.
  • Aggregations with GROUP BY / HAVING for reporting questions.
  • Rewriting slow queries and explaining what changed.
  • Schema design: tables, constraints, indexes and migrations.

Tip: Already have a query that misbehaves? Use the PostgreSQL Code Explainer to understand it, or the PostgreSQL Code Reviewer to find what's wrong with it.

Other SQL dialects: SQL SQLite MySQL PL/SQL T-SQL

When to enable Web Access and Code Execution

These tools provide different kinds of context and verification. Enable them when they improve the task.

Web Access

Use for current docs

Enable Web Access when the task depends on current documentation, an external API, or a third-party package—especially a new, niche, or less familiar library.

For the best result

  • Paste the official documentation URL into your prompt.
  • Name the package and version you intend to use.
  • Ask the model to follow the linked API instead of relying on memory.
  • For multiple sources, say which source is authoritative.

Example: “Use version 4.x and follow the official documentation at https://docs.example.com/.”

Code Execution

Use for automatic checks

Enable Code Execution when you want the model to run the code, execute tests, reproduce an error, or compare the result with an expected output.

Particularly useful for

  • Algorithms with testable inputs and outputs.
  • Parsing, data transformation, and numerical tasks.
  • Debugging a reproducible error.
  • Checking that dependencies install and tests pass.

Credit note: Running and iterating on code may consume more credits than a single response alone. Leave execution off when you only need a small snippet you can inspect yourself.

Keep building
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Browse public code generations for inspiration, or contact us if you have any questions.