// Topics / Postgresql

Postgresql

Definition

Postgresql coverage in this archive spans 11 posts from Apr 2016 to May 2022 and centers on data correctness and operability under real production constraints. The strongest adjacent threads are databases, architecture, and performance. Recurring title motifs include database, postgresql, migrations, and without.

Key claims

  • The common theme is that schema, ownership, and query shape drive most downstream outcomes.
  • Early posts lean on database and sharding, while newer posts lean on database and postgresql as constraints shifted.
  • This topic repeatedly intersects with databases, architecture, and performance, so design choices here rarely stand alone.

Practical checklist

  • Define freshness, correctness, and latency targets before choosing storage or pipeline patterns.
  • Start with the newest post to calibrate current constraints, then backtrack to older entries for first principles.
  • When boundary questions appear, cross-read databases and architecture before committing implementation details.

Failure modes

  • Scaling pipelines before locking down source-of-truth and reconciliation behavior.
  • Optimizing single queries while ignoring data model drift and access patterns.
  • Applying guidance from 2016 to 2022 without revisiting assumptions as context changed.

Suggested reading path

References

    PostgreSQL Performance: Measure First, Tune Second Most Postgres performance problems are indexing problems. The rest are vacuum problems. Here's how to find and fix both. postgresql databases performance Zero-Downtime Database Migrations Without the Drama Database migrations are the one place where a single ALTER TABLE can ruin your weekend. Here's how to do them safely with expand-and-contract, batched backfills, and compatible deploys. databases migrations zero-downtime Database Reliability Engineering: What I've Learned the Hard Way Practical database reliability from running Postgres at the fintech startup and at large enterprises. Includes config examples, migration patterns, and the operational habits that actually prevent outages. databases reliability sre Most Teams Should Just Use Postgres Serverless databases are solving problems most teams don't have. Here's why Postgres with a connection pooler is still the right answer. serverless databases postgresql Database Replication Patterns That Actually Matter A practical breakdown of replication modes, topologies, and the tradeoffs between consistency, availability, and not losing your users' data at 3am. databases replication postgresql The PostgreSQL Tuning Playbook I Actually Use Battle-tested PostgreSQL tuning from running fintech and startup workloads: connection pooling, memory sizing, index discipline, vacuum management, and the queries that tell you what's broken. postgresql database performance Database Sharding: You Probably Don't Need It Yet Most teams shard too early. Here's how we thought about it at the fintech startup, when it actually makes sense, and the SQL-level decisions that matter most. database postgresql sharding Stop Guessing: How I Fix Slow Databases The repeatable process I use at the fintech startup to diagnose and fix database performance problems instead of throwing random indexes at the wall. databases performance postgresql The Economics of State: Why Scaling Up Beats Sharding (Until It Doesn't) A production-grounded case for exhausting single-server headroom with pooling, replicas, and partitioning before taking on sharding complexity. postgresql databases scaling Database Migrations Without Downtime A practical guide to evolving schemas without maintenance windows by keeping old and new code compatible at every step. databases migrations postgresql Postgres vs MySQL in 2016: A Practical Comparison A grounded look at PostgreSQL and MySQL as of April 2016, focusing on integrity, query power, and operational tradeoffs rather than benchmark hype. postgresql mysql databases