Questions? Answers.
Can't find what you're looking for? Reach out.
Why switch from BigQuery Studio?
BigQuery Studio works. Querylab.io makes you faster. Real-time completions from your actual schema, errors caught before you run, cost estimates on every query. The difference between functional and productive.
Can I try it before committing?
There is nothing to commit to — Querylab.io is free, including commercial use. No credit card, no trial timer, no seat count. The Playground lets you explore without even connecting BigQuery.
Can my own AI tool query BigQuery through Querylab.io?
Yes. The desktop app runs a local MCP server, and Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor and VS Code each connect to it with one button. Every call they make is held to the limits you set: a maximum GB per query, a daily limit for AI tools, per-dataset rules, and writes that wait for your approval. The MCP activity tab lists every call with what it billed and what it cost.
What makes Prism AI better than Cursor with MCP?
You can have both: the desktop app's MCP server lets Cursor or Claude Code query BigQuery through your cost limits. What Prism AI adds is the rest of the work in one window. It searches your real schema before it writes SQL, dry-runs what it writes, puts the price on the Run button, and leaves the result in a grid with history and exports.
How does it reduce BigQuery costs?
Development Mode samples data for 80–95% cheaper testing. Budget limits block runaway queries. Per-CTE breakdown pinpoints what's expensive. Smart recommendations for reservation vs. on-demand billing.
How long does it take to get started?
Two minutes. Sign in with Google, authorize BigQuery, start writing. No installation, no config, no onboarding calls. Schema loads automatically.
Is there a desktop app?
Yes — currently in beta for macOS (Apple Silicon), with Windows next. Credentials stay local in your OS keychain, hotkeys are native, Prism AI drives the agent already on your machine, and the local MCP server lets that agent query BigQuery inside your limits.