Normalization vs Denormalization vs CQRS
This is a dev post classified by Jev as Databases (a tutorial), kept by the Dev Radar because it carries real work, not commentary.
Normalization vs Denormalization vs CQRS (explained in 2 mins or less) Normalization Store each fact once. Split data into clean tables (users, orders, items) and join when you read. Great for writes and correctness. Painful for heavy-read dashboards. Joins can get expensive. Denormalization Copy useful fields into the same row so reads are fast. Example: store user_name on every order. Great for reads. Writes get messier. One update may touch many places, and data can drift. CQRS (Command Query Responsibility Segregation) Don’t pick one shape for everything. • Writes go to a norma
Posted by Akintola Steve (14.2k followers) 1 h ago · 12 likes · 456 views · view the original post on X. Kept by the Dev Radar as Databases.
More dev work like this
- Hundreds of AI agents hitting your retrieval layer at once changes the problem entirely.… — @thenewstack
- A normal database finds exact matches. Search "cafe" and you get rows containing the… — @hrswatigupta
- Your database bill is eating your runway. — @suraj_sharma14
- Got 18M requests 🤯 on this from GoogleOther bot. Now Blocked with few clicks in @vercel… — @rishi_raj_jain_
- Essential SQL concepts #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT… — @Sheraj99
- SQL basics you must know #BigData #Analytics #DataScience #AI #MachineLearning #IoT… — @Sheraj99
- Construct a bitemporal knowledge graph with Utopia that evolves as material arrives and… — @tom_doerr
- Jev at dating: https://date-with-jev.vercel.app 💔 — @rishi_raj_jain_
Every post is read and classified by Jev (TypeSafe): what it is, which market it belongs to, and whether the link is a real tool. 15.4k posts from 4.9k X accounts over the last 21 days, 1.7k tools, 12 markets. Collected every 5 minutes, fully re-ranked every hour — last update 2026-09-20 14:59 UTC. Full method.