Handling Massive PostgreSQL Databases: Zerodha’s Scaling, Sharding & Performance Secrets | Blog
Source: https://zerodha.tech/blog/working-wit...
How do India’s leading fintech companies handle gigantic databases powering real-time financial apps? In this deep dive, discover how Zerodha engineers manage and scale 20TB+ PostgreSQL databases for millions of users—serving 40,000+ queries per second during peak trading! 🚀
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*In this video, you’ll learn:*
Real-world PostgreSQL architecture for huge, historical financial datasets
How Zerodha shards, partitions, and manages tens of billions of rows
Pro tuning tips: `work_mem`, `shared_buffers`, `vacuum`, and indexing strategies
Zerodha’s approach to denormalization, materialized views, and minimizing JOINs
Using PostgreSQL as a hot cache to handle massive reporting loads
Practical lessons: when to go multi-shard, what to avoid, and performance tradeoffs
Why understanding vacuuming and indexing is more important than jumping to distributed databases
*Chapters:*
0:00 Intro – Why PostgreSQL at scale?
1:12 Zerodha’s database growth story
3:40 Schema decisions: denormalization & logical partitions
6:22 The art of tuning memory & connections
10:00 Vacuuming, indexing, and table health
13:33 Sharding, hot cache with PostgreSQL, and SQL Jobber
17:00 Practical lessons and engineering best practices
Perfect for DBAs, backend engineers, fintech architects, or anyone building or scaling large PostgreSQL deployments!
#PostgreSQL #DatabaseEngineering #Zerodha #Fintech #DataEngineering #Sharding #DBAPerformance #BackendEngineering
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Inspired by Zerodha Tech’s blog: “Working with PostgreSQL.” Full article link in pinned comment.