Day 14/30: Indexing & Query Optimization 📌
This is a dev post classified by Jev as Databases (a tutorial), kept by the Dev Radar because it carries real work, not commentary.
Day 14/30: Indexing & Query Optimization 📌 Your database can have millions of rows. The problem is: How do you find the data quickly? That's where indexes come in. An index is a data structure that helps the database find rows without scanning the entire table. Without an index: → Scan millions of rows → Find matching records → Slow query With an index: → Look up the indexed value → Jump closer to the required rows → Much faster query Common indexes: → B-Tree → Hash → Composite index → Unique index Example: SELECT * FROM users WHERE email = 'user@example.com'; An index on `email`
Posted by SCR (7.3k followers) 4 days ago · 74 likes · 1.9k views · view the original post on X. Kept by the Dev Radar as Databases.
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