I indexed 17,341 polynomial fan curves in Postgres and matched a duty point in <100ms

1. 1Build a database schema to store polynomial fan curves in Postgres
2. 2Use Postgres indexing to optimize query performance
3. 3Configure a query to match a duty point in under 100ms
4. 4Test the query performance with a large dataset of fan curves
5. 5Apply this approach to other large datasets with similar query requirements

Data engineers and developers working with large datasets can benefit from this approach to improve query performance, while product managers can apply this to optimize product catalogs

💡 Proper indexing and database schema design can significantly improve query performance in large datasets

🚀 Indexed 17,341 polynomial fan curves in Postgres and achieved <100ms query time! 💡