PostgreSQL performance and cost across 23 EC2 instance types
Hey! I'm Andrei. I got frustrated by how people tend to build overcomplicated backend systems, being "motivated" by big tech case studies and popular books. So, I started exploring lean architecture, and building my digital garden of ideas, approaches and data that align with this direction. Here I want to present one of the tools – Sizing tool for PostgreSQL. I've benchmarked PostgreSQL on different EC2 instances and disks, with different initial data sets to see performance that these instances can give you. And I've built a tool to visualize this data, which I welcome you to explore. So,…
In plain words
This tool helps developers choose the most cost-efficient AWS EC2 instance for PostgreSQL databases by visualizing performance benchmarks across 23 instance types and different disk configurations. Users input parameters like required requests-per-second and disk size to find optimal sizing recommendations. It's designed for engineers building simpler backend systems who want data-driven instance selection instead of over-provisioning based on industry case studies.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hey! I'm Andrei. I got frustrated by how people tend to build overcomplicated backend systems, being "motivated" by big tech case studies and popular books. So, I started exploring lean architecture, and building my digital garden of ideas, approaches and data that align with this direction. Here I want to present one of the tools – Sizing tool for PostgreSQL. I've benchmarked PostgreSQL on different EC2 instances and disks, with different initial data sets to see performance that these instances can give you. And I've built a tool to visualize this data, which I welcome you to explore. So, you can put your usual input parameters, like needed RPS and disk size as input, and find out which instance will be the most cost-efficient for your needs. You can read about the methodology here: https://postgres.saneengineer.com/about I've tested one workload – mixed 90/10 read/write, and only selected configurations. But it is extensible, and I (and you – benchmark is open source: https://github.com/anivaniuk/sanebench) can run more configurations to have more data represented. Does it look interesting? What workload should I benchmark next?
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