Question: Can you recommend a tool that generates realistic seed data for relational databases to speed up development and testing?

If you need a tool to generate realistic seed data for relational databases, Snaplet is a great option. It uses AI to generate production-like data, which can save developers time and improve the quality of their work. Snaplet supports PostgreSQL, SQLite, MySQL and other databases, offers instant seed data generation, type safety and production-like data transformation. It's designed to work well with local development environments, end-to-end testing and debugging, with several pricing tiers including a free option.

Another contender is Tonic, which speeds up engineering velocity by generating realistic, secure test data that's as complex as production data without compromising privacy. Tonic ensures consistency and freshness across environments and can transform data, making it a good fit for staging environments and local development. It can integrate with relational databases, NoSQL databases, data warehouses and other sources, and offers a pay-as-you-go pricing plan starting at $199 per month.

If you need something more flexible, check out Gretel Navigator, which can generate, edit and amplify tabular data. It can run in Create mode to generate plausible data when none exists and Edit mode to modify, amplify or interpolate data with SQL or natural language prompts. That makes it useful for training foundation models, fine-tuning language models and creating evaluation datasets.