Your API is fast. Your code is clean. Your architecture looks solid on paper.
Then you hit 500,000 records and everything slows down. Queries that ran in 12ms now take 4 seconds. Your dashboards lag. Users start filing support tickets. Your on-call engineer is staring at a query plan at midnight wondering what went wrong.
Nine times out of ten, the answer is indexing. Not missing indexes — wrong indexes. Indexes that exist but don't help. Indexes that actively hurt write performance without meaningfully improving reads.
This is a breakdown of the most damaging database indexing mistakes in production SaaS systems — and how to fix them before they become incidents.
Mistake 1: Indexing Everything "Just in Case"
