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Over 15 years later, some solutions are still great solutions Introduction

OpenAI recently shared their story about how they scaled to 800 million users on their ChatGPT platform. With the boom of AI in the past year, they’ve certainly had to deal with some significant scaling challenges, and I was curious how they’d approach it. To sum it up, they addressed the following issues with the following solutions:

A major architectural milestone that removes schema logs and simplifies how pgstream captures and replicates Postgres schema changes

PostgreSQL 18 introduces native "Skip Scan" for multicolumn B-tree indexes, a major optimizer enhancement. However, a common misconception is that pre-v18 versions purely resort to sequential scans when the leading column isn't filtered. In reality, the cost-based planner has long been capable of leveraging such indexes when efficient.

How it works under the hood:

The following thoughts and comments are completely my personal opinion and do not reflect my employers thoughts or beliefs. If you don’t like anything in this post, reach out to me directly, so I can ignore it ;-).