Using UUID as a primary key in MySQL inflates index size, causes random inserts that trigger frequent index and page splits, slows both insert and query operations, and makes updates costly, but techniques such as ordered UUIDs, binary storage, hybrid auto‑increment keys, and table partitioning can mitigate these issues.
This article experimentally compares auto‑increment, UUID and Snowflake‑generated primary keys in MySQL, analyzes their index structures, shows insertion‑time benchmarks, discusses the trade‑offs of each approach, and concludes that sequential auto‑increment keys deliver the best overall performance.
This article explains why defining MySQL table columns as NOT NULL—unless business logic demands NULL—improves query speed, reduces storage overhead, enhances index efficiency, prevents aggregation distortion, simplifies application code, and strengthens data consistency, while also noting scenarios where NULL is appropriate.
The article explains why using UUIDs as primary keys in MySQL large tables leads to poor index efficiency, slower inserts and queries, and costly index refreshes on updates, and then presents practical optimization techniques such as ordered UUIDs, binary storage, hybrid auto‑increment keys, and table partitioning.
