PostgreSQL can scale extremely well in production, but many deployments run on conservative defaults that are safe yet far from optimal. The crux of performance optimization is to understand what each setting really controls, how settings interact under concurrency, and how to verify impact with real metrics.
This guide walks through the two most important memory parameters:
shared_buffers
work_mem
shared_buffers
Let’s start with shared_buffers, because this is one of the most important concepts in PostgreSQL. When a client connects to PostgreSQL and asks for data, PostgreSQL does not read directly from disk and stream it back to the client. Instead, PostgreSQL does something that pulls the required data page into shared memory first and then serves it from there. The same design applies to writes. When the client updates a row, PostgreSQL does not immediately write that change to disk. It loads the page into memory, updates it in RAM, and marks that page as dirty. Disk writes come later.
And this design is intentional because reading and writing in memory are orders of magnitude faster than reading from or writing to disk, and it dramatically reduces random I/O overhead.
So what exactly is shared_buffers?
shared_buffers defines the size of the shared memory region that PostgreSQL uses as its internal buffer cache. And all the reads and writes go through shared_buffers. Disk interaction happens later asynchronously through background writing and checkpoints. So shared_buffers is the layer between the database processes and the disk.