PostgreSQL Performance Boost: Fixing a 3,000x Speedup

⚡ A Slow PostgreSQL Query Taught Me a Big Performance Lesson A business-critical report query was taking 18 minutes in production. The issue was not PostgreSQL. It was our approach. Here’s what fixed it 👇 ✅ Used EXPLAIN ANALYZE to find sequential scans ✅ Added composite indexes on filter columns ✅ Rewrote nested subqueries into joins ✅ Reduced unnecessary type casting ✅ Removed unused columns from SELECT ✅ Ran VACUUM ANALYZE to refresh planner stats 🎯 Result: The same query dropped from 18 minutes → 11 seconds That’s the power of query plan analysis + indexing strategy. The best tuning lesson I learned: Don’t guess. Read the execution plan. What is the biggest performance gain you achieved in PostgreSQL? #PostgreSQL #PerformanceTuning #SQL #DatabaseOptimization #EXPLAINANALYZE #TechLeadership

📣 PG Phriday is here! What is a collation—and why might it make your data look corrupt? It’s one of those PostgreSQL topics that’s easy to overlook… until something breaks. In this week’s post, we unpack how collations control how text is sorted and compared—and how subtle changes (like OS or library updates) can lead to incorrect query results or even index corruption. If you’re working with text data in Postgres and want to avoid hard-to-diagnose issues, this is a must-read. 🔗 Check it out: https://hubs.la/Q049zryc0 #PostgreSQL #Postgres #PGPhridays #Database #Performance #pgEdge Shaun Thomas

Even I didn't really understand the full extent of collation-driven corruption until I started investigating for this article. Yeah, everyone knows glibc 2.28 kind of screwed the pooch, but it goes _much deeper_ than that. I also found out, surprisingly, that glibc collations are _still the default_ despite all of the damage it's caused over the years. I talk a lot about the history, the aftermath, and what you can do going forward to protect yourself. Have a look!

🚨 PostgreSQL Mistake That Kills Performance 🚨 You created an index… But your query is STILL slow? Here’s why 👇 👉 PostgreSQL is NOT using your index. Example: CREATE INDEX idx_users_email ON users(email); But your query: SELECT * FROM users WHERE LOWER(email) = 'test@gmail.com'; ❌ Index NOT used. Why? Because PostgreSQL sees this as: LOWER(email) ≠ email So your index becomes useless. --- ✅ Solution: Create a FUNCTIONAL INDEX: CREATE INDEX idx_users_email_lower ON users(LOWER(email)); Now PostgreSQL can use the index ⚡ --- 💡 Real-world lesson: Indexes only work when your query matches the index EXACTLY. Even small changes like: - Functions (LOWER, UPPER) - Type casting - Calculations …can break index usage. --- 🔥 Pro Tip: Always check your query plan: EXPLAIN ANALYZE SELECT ... Don’t assume your index is working. VERIFY it. --- Small awareness. Huge performance gain. #PostgreSQL #SQL #PerformanceTuning #Database #DataEngineering #Backend #TechTips

Postgres' EXPLAIN command is even more powerful than I thought https://lnkd.in/di2BrWx5 At this point, it can probably tell you what you ate before running the query.

Most people think PostgreSQL performance issues are complex. In reality, many of them come down to one simple mistake 👇 👉 Not checking execution plans. Before trying to optimize any slow query, always run: EXPLAIN ANALYZE SELECT * FROM transactions WHERE user_id = 123; 💡 This tells you: - Whether indexes are being used - If a sequential scan is happening - Actual execution time vs expected I’ve seen cases where: A query taking 5+ seconds Was reduced to milliseconds Just by adding the right index after checking the plan. 📌 Lesson: Don’t guess. Don’t assume. Let PostgreSQL tell you what’s wrong. #PostgreSQL #SQL #DBA #Performance #DataEngineering

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.

I'm documenting everything I know about Postgres — from scratch. Not tutorials. Not docs summaries. A real, living series that builds layer by layer — with the production gotchas, the mistakes engineers actually make, and quizzes to test yourself as you go. 🐘 Postgres Internals — what's published so far: Part 01 — Tables, Types & Constraints Why TIMESTAMP without a timezone will ruin your life. Why FLOAT has no business near money. And why your CHECK constraints should live in the database, not your API. Part 02 — Views & Materialized Views A view is a reusability tool. A materialized view is a performance tool. Knowing which one to reach for — and when — is the difference between a fast dashboard and a very unhappy database. Each post has a quiz at the end with a "Show Answer" button. But you have to pinky swear you answered first 🤙 Coming next: Indexes, EXPLAIN ANALYZE, Transactions & Locking, Replication, and Postgres at scale. 👉 https://lnkd.in/gSA8sqrr Who else is doing a Postgres deep-dive? Drop your favourite gotcha below 👇 #Postgres #DatabaseEngineering #BackendDevelopment #SystemDesign #SoftwareEngineering

🚨 New Medium Article Alert! Ever wondered what actually happens behind the scenes when you run a simple SELECT query in PostgreSQL? We write queries every day… SELECT * FROM users WHERE id = 42; But under the hood, PostgreSQL is doing a LOT more than just fetching rows. In my latest article, I break it down in a simple, visual, and easy-to-understand way: 🔍 What happens after you hit enter ⚙️ How the query parser, planner, and executor work 📊 Why indexes matter 🚀 How PostgreSQL optimizes your queries for performance If you're working with databases, backend systems, or building data pipelines — this is something you must understand. 💡 Whether you're a beginner or an experienced engineer, this will change how you think about query performance. 👉 Read the full article here: https://lnkd.in/gRkF_gZk #PostgreSQL #Databases #BackendEngineering #SystemDesign #PerformanceOptimization #SQL #TechExplained