PostgreSQL Performance Optimization Strategies

Why Your Database Indexes Might Be Hurting You Most engineers add indexes to speed things up. Few ever audit whether those indexes are actually being used. Here's what I've seen in production PostgreSQL systems: - Duplicate indexes silently eating write performance - Partial indexes ignored because the query planner chose a seq scan anyway - Composite indexes with columns in the wrong order, making them useless for 90% of queries Run this today: SELECT schemaname, relname, indexrelname, idx_scan, pg_relation_size(indexrelid) AS index_size FROM pg_stat_user_indexes WHERE idx_scan = 0 ORDER BY pg_relation_size(indexrelid) DESC; That query shows you every index that has never been used since the last stats reset, sorted by size. I've seen teams reclaim 30%+ storage and noticeably improve write throughput just by dropping dead indexes. The best engineers don't just add indexes. They treat them like code: review them, measure them, and delete them when they stop earning their keep. What's the worst "performance optimization" you've found that was actually making things slower? 🧑🏻💻 You can find the code snippet here: https://lnkd.in/eRz5vccD Don't worry, I am working on my URL Short-ner Service, it will be up soon. 😅 PS. Graphic generated by Claude. #postgresql #systemdesign #backend #softwareengineering

⚡ Ever wondered how database changes are recorded before your CDC pipeline ever sees them? Change Data Capture (CDC) is one of those ideas that sounds complex until it clicks. Instead of batch-syncing data on a schedule, you capture every insert, update, and delete the moment it happens and stream it downstream in near real time. In my latest post I write about how the Write-Ahead Log (WAL) in #PostgreSQL (the world's most popular open-source OLTP database) works under the hood and how it enables CDC. You do not need to be building a specific pipeline to find this useful. The WAL affects every PostgreSQL operation, and understanding it changes how you think about performance, recovery, and observability. 👉 Blog post: https://lnkd.in/eVRZVumk #databases #dataengineering #cdc

New piece on CI-enforced standards: how we use a real Postgres instance and a few SQL checks to make missing indexes, drifted migrations, and rogue camelCase columns fail the build before review. https://lnkd.in/dhfkUd8E

PostgreSQL continues to close a long-standing operational gap with REPACK CONCURRENTLY — a major step forward for managing table bloat in always-on environments. Table bloat is a real challenge in high-write PostgreSQL systems. Until now, options included: • VACUUM — safe but limited • VACUUM FULL — blocking • pg_repack — external tool • pg_squeeze — extension-based concurrent rewrite Now, REPACK CONCURRENTLY brings this capability closer to PostgreSQL core. Interestingly, this work is heavily inspired by pg_squeeze — designed by the same author, using logical decoding and background workers to rewrite tables without blocking workloads. Why this matters: • Always-on maintenance • Reduced operational risk • Better performance predictability • Enterprise-grade PostgreSQL operations This is another step in PostgreSQL’s evolution — from a powerful database to a self-managing enterprise data platform. Small feature. Big operational impact. Commit: https://lnkd.in/eN_cFTpm #PostgreSQL #OpenSource #Database #Postgres #DBA #CloudNative #DataPlatform #DatabaseEngineering

The cool part, IMO, is the extension / tool to core-feature path. Adding major changes to core is challenging, so proving out the concept in an extension / tool first and providing this value in the ecosystem is a great path forward. A lot of folks who suggest new Postgres contributions are disappointed when they get “this sounds like an extension” as a response, but it’s actually good advice.

The biggest myth about PostgreSQL is that indexing is a silver bullet for query performance. Many teams believe that simply adding more indexes will lead to better SQL optimization. However, this misconception can lead to bloated databases and slower write operations. In fact, excessive indexing can increase the complexity of data maintenance and degrade performance during data modifications. To effectively optimize your PostgreSQL database: - Analyze query patterns to determine which indexes are truly necessary. - Implement partial indexes to boost performance without adding overhead. - Utilize connection pooling to manage database connections efficiently and reduce latency. - Consider sharding your database for improved scalability, especially with high-traffic applications. - Regularly review and refine your indexing strategy to align with evolving data access patterns. - Explore replication strategies to enhance read performance and disaster recovery capabilities. How are you balancing indexing with the need for performance in your PostgreSQL deployments? Building production-grade automation | CODE AT IT #PostgreSQL #DatabaseEngineering #SQLOptimization #TechLeadership #SoftwareArchitect

Postgres now has the ability to export statistics about a database. Here's a great post about how to use this ability to debug and optimize production database queries in test databases: https://lnkd.in/eMptU8J7

Coming up soon at #PostgresConf (both in-person and online)... 🍿 "Past, Present, and Future: Logical Decoding and Replication in PostgreSQL", presented by Hari Kiran, will cover topics like: 📖 the journey of logical decoding and replication in PostgreSQL, from its early adoption through extensions like pglogical, to the robust native features introduced in recent PostgreSQL releases ⚙️ innovations in the ecosystem, particularly the work of Multi-master replication, that are shaping the future of distributed PostgreSQL Learn more about the session coming up - watch his announcement, or check out the program ➡️ https://hubs.la/Q04b0xdd0 #postgresql #postgres #technews #data #sql #dataengineering #devops #opensource #techevent #postgresconf #postgresworld

Moving to a new database sounds easy, right? I thought the same—until I dove deep into the challenges and hidden pitfalls. It's way harder than just copying files. You need to extract millions of rows without slowing down production. You need to make sure nothing gets lost or duplicated. And you need the whole thing to work seamlessly with a completely different database engine. Researching the problem space and exploring YugabyteDB’s solution has been both insightful and inspiring, showcasing a powerful approach to solving complex distributed database challenges. Heres how Yugabyte 𝗩𝗼𝘆𝗮𝗴𝗲𝗿 solves the crucial issue—but here's the clever part: instead of reinventing the wheel, it leverages PostgreSQL's existing tools. The architecture is simple: Voyager runs on its own machine (not on your database servers), connects over the network, and orchestrates the whole migration without risking your production system. This "𝘂𝘀𝗲 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝘁𝗼𝗼𝗹 𝗳𝗼𝗿 𝗲𝗮𝗰𝗵 𝗷𝗼𝗯" philosophy is worth studying, regardless of whether you're moving databases or building distributed systems. The result? A migration engine that's both 𝗽𝗼𝘄𝗲𝗿𝗳𝘂𝗹 𝗮𝗻𝗱 𝗽𝗿𝗮𝗴𝗺𝗮𝘁𝗶𝗰. For a deeper understanding and more insights, check out my full article : https://lnkd.in/gEpbVA6B

Performance optimization, database design, and scalability - three areas my experience as a DBA has deeply rooted in me. I recall the days when I had to ensure our PostgreSQL database could handle a sudden surge in traffic, and the strategies we employed to scale it vertically and horizontally. From configuring connection pooling to implementing effective indexing, every tweak counted. One of the most significant lessons I learned was the importance of monitoring and analyzing database performance metrics to identify bottlenecks before they became major issues. In my previous role, I worked with a team to migrate our database to a distributed architecture, which greatly improved our database's ability to handle high traffic and large data volumes. The journey was not without its challenges, but the outcome was well worth the effort. If you're interested in learning more about database scalability and optimization, I highly recommend checking out some of the insightful articles on www.person-it.com/blog. The blog offers a wealth of information on database management and IT trends, and I often find myself referring back to it for inspiration and new ideas. With the ever-evolving landscape of database technology, staying informed is key to staying ahead. #PostgreSQL #DatabaseScalability #DatabaseOptimization #DBA #ITblog #DatabaseManagement