Add Indexes to Speed Up WHERE Clauses

When querying large tables, SQL performance often breaks down during filtering operations—especially those using WHERE clauses on non-indexed columns. If you're filtering a table like orders by customer_id, your database may be performing a full table scan to find matches, which gets expensive as the dataset grows.

Adding an index to columns commonly used in filters—like customer_id, user_id, or email—can drastically reduce scan time. Instead of reviewing every row in the table, the database engine can use the index as a shortcut to jump directly to relevant rows. This improves lookup time and overall query execution by several magnitudes.

In the example below, a query without indexing requires a full scan of the orders table. By introducing an index on customer_id, the database uses a B-tree to locate rows in logarithmic time, dramatically improving efficiency. In most PostgreSQL, MySQL, and SQL Server environments, this change alone can lead to 2–10x speed gains.

While indexes can significantly boost performance, they also increase storage usage and write time, so apply them to high-read, low-write fields with good selectivity. Tools like Galaxy can help detect these optimization opportunities automatically and recommend indexes based on query patterns.