We Moved Cazpian's Spark Pools to ARM — 2x Faster Under Load
· 12 min read
Conventional wisdom says migrating a data engine to ARM is a performance gamble you take for the discount. We ran the experiment on our own Spark compute pools, and the result inverted the premise: under 100-way concurrency, the ARM64 pool ran every job roughly twice as fast as its x86 twin — at about 20% lower infrastructure cost.
We are publishing the numbers, but also the part benchmark posts usually cut: our first measurement said ARM was 8.5x slower, and that number was wrong in a way that had nothing to do with ARM. If you are planning an ARM migration for your data platform, the detour is probably worth more to you than the table.