What is Database Indexing?
A database index is a data structure that speeds up queries by letting the database find rows without scanning the entire table. It trades a small amount of storage and write speed for dramatically faster reads.
In plain English
An index works like the index in the back of a textbook. Instead of reading every page to find 'authentication,' you look it up in the index and jump straight to page 47. Without it, the database reads every row — every page — to find what you need.
How it works
When you create an index on a column, the database builds a sorted copy of that column's values alongside pointers to the full rows. When a query filters or sorts by that column, the database uses the index instead of scanning the table. The most common index type is a B-tree, which supports equality and range queries efficiently.
Why it matters for AI-built apps
AI-generated database schemas often omit indexes, leading to queries that work fine in development with 100 rows but crawl in production with 100,000. Slow queries degrade user experience, increase server load, and can cascade into full outages. Adding the right indexes is one of the highest-ROI performance improvements you can make.
Best practices
Index columns you filter, sort, or join on frequently — especially foreign keys. Avoid over-indexing: every index slows down writes slightly and increases storage. Use your database's query analyzer (EXPLAIN in PostgreSQL/MySQL) to confirm indexes are actually being used.
Frequently asked questions
Can I add indexes without downtime?
PostgreSQL supports CREATE INDEX CONCURRENTLY which builds the index without locking the table. Most modern databases have equivalent options.
How do I know which columns to index?
Look at your slowest queries first. Any column in a WHERE, ORDER BY, or JOIN clause on a large table is a candidate.
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