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data-peek

★ 0 updated 4mo ago ⑂ fork

A minimal, fast, database client desktop application. Built for developers who want to quickly peek at their data without the bloat.

Data Peek

Data Peek is a lightweight desktop application that lets you browse and query your databases without opening a heavy IDE. Instead of spinning up a full development environment, you can launch it in seconds and start exploring your data, running SQL queries, and analyzing performance—all from a clean, distraction-free interface.

The app works by connecting directly to your database servers (PostgreSQL, MySQL, SQL Server, or SQLite) so you can see tables, run queries, and even edit data on the fly. It includes an AI assistant that can translate plain English questions into SQL, generate charts from your results, and suggest performance improvements if a query is running slowly. You can also visualize how your tables relate to each other with automatic relationship diagrams, explore query performance with detailed breakdowns, and save frequently-used queries for quick access later.

Security and speed are central to the design. Your database credentials are encrypted and stored on your computer—nothing leaves your machine or gets sent to external servers (except when you opt in to use AI features with your own API keys). The app opens and runs queries much faster than traditional SQL clients because it strips away the bloat. You also get keyboard shortcuts for power users, a command palette for rapid navigation, and the ability to work with multiple queries and databases at the same time across different tabs and windows.

The ideal user is a developer or data analyst who frequently needs to inspect databases during development, debugging, or data exploration. Instead of juggling command-line tools, clunky web UIs, or heavy database managers, they can pull up Data Peek, connect to a database in seconds, write a query with autocomplete help, and see the results immediately. If they want to understand why a query is slow, they can view the query plan and execution timeline. If they want to ask "What's our average order value last month?" they can ask in English and let the AI generate the SQL.