Transactional databases represent one of the most important workloads run in data centers today, and they depend on high performance storage. This performance brief details tests of the KIOXIA PM7 SAS SSDs compared to common legacy SATA SSDs:

A database knows where your data is. A vector database understands what your data means. It finds information based on similarity and meaning, not just exact keywords, powering semantic search, RAG, recommendations, and agent memory. See how it works:

Every database writes, stores, and reads data. So why do you need to pick between 50 different ones? The key is the layout and performance of that database. Do you want it to write fast or read fast? Do you want to know which user placed which order or do you want to sum and count all orders. @dumkydewilde tells you why you need another ducking database, and what kind of performance optimizations and tricks @duckdb uses to be both fast and cheap. In the end the useful question is not which database is best. It's which question you are going to ask a thousand times a day.

we just retired one database column. 88 million fewer calls per day. p90 is now 61ms. a massive migration, zero downtime. super proud of the changes we’re pushing to make @resend the fastest and most reliable email platform.

A 2,500 GB database with a 20 GB hot working set doesn’t need 2,500 GB of RAM. That principle runs through Lakebase Postgres cost optimization: size around what your application actually needs. ✦ Sync only the working set your app queries ✦ Match Snapshot, Triggered or Continuous sync to freshness requirements ✦ Size compute so hot data fits in cache ✦ Set PITR and snapshots around actual recovery needs The full guide breaks down how to keep costs predictable while maintaining the performance, availability and developer experience applications need: