OpenAI has scaled PostgreSQL to support over 800 million active users of ChatGPT, making it one of the largest PostgreSQL deployments globally. The database can handle millions of concurrent connections and a very high volume of requests per second. OpenAI employs several strategies to optimize performance:
1. **Connection Pooling with PgBouncer**: Reduced database connections from 10,000 to 200, enhancing efficiency by a factor of 50.
2. **Read Replicas**: Distributes read requests across multiple replicas while the primary database handles writes.
3. **Horizontal Sharding**: Partitions data across multiple instances based on a shard key, such as user_id or tenant_id.
4. **Query Optimization**: Analyzes slow queries and creates appropriate indexes to maintain performance.
5. **Connection Management**: Implements timeouts and connection limits to prevent overload.
6. **Caching**: Uses application-level caching with Redis to reduce database load.
7. **Monitoring and Observability**: Tracks key metrics like connection counts and query latency to identify issues early.
These strategies enable OpenAI to maintain performance and reliability for a large user base.