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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, 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/aboutI'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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FL score

62

out of 100

Verdict

VALIDATE

medium confidence

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A PostgreSQL benchmarking tool that helps engineers pick cheaper EC2 instances by showing real performance data instead of guessing.

The pain

Engineers waste money on oversized database instances because they don't know what performance they actually get from smaller, cheaper options. They either overprovision out of fear or underprovision and hit limits in production.

The gap

AWS provides specs but not real-world PostgreSQL performance data across instance types. Engineers either run their own benchmarks (expensive, time-consuming) or copy what big tech companies do (irrelevant to their scale).

Build angle

Position this as a reference tool for cost optimization decisions, not a general benchmarking platform. Start by proving ROI on a specific, common workload (e.g., SaaS backends with 90/10 read-write). Build a community around contributing benchmarks for other workloads rather than trying to cover everything yourself.

Strengths

  • Solves a real, recurring decision point that engineers face repeatedly
  • Open source benchmark code removes trust barrier and enables community contribution
  • Methodology is transparent and reproducible, which matters for infrastructure decisions
  • Addresses a lean architecture philosophy that resonates with indie hackers and bootstrapped companies
  • Low barrier to entry, tool is free and doesn't require signup

Risks

  • Market size unclear: how many engineers actually make instance-type decisions vs. using defaults or hiring DevOps?
  • Monetization path is murky, this looks like a free tool with no obvious revenue model
  • Benchmark data becomes stale quickly as AWS releases new instances and PostgreSQL versions change
  • Only tested one workload (90/10 read-write); most real systems have different patterns (OLTP, batch, time-series, etc.)
  • Competitive threat from AWS's own cost optimization tools and third-party cloud cost platforms
  • Requires ongoing maintenance to stay relevant; one-person project may not sustain this

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