Cassandra

In 1996, Patrick O’Neil and his colleagues at the University of Massachusetts Boston published a paper describing a data structure that would take nearly a decade to find widespread adoption. The Log-Structured Merge-Tree (LSM-Tree) was designed to solve a problem that barely existed at the time: how to efficiently index data when writes vastly outnumber reads. Today, LSM-Trees power the storage engines of Cassandra, RocksDB, LevelDB, HBase, InfluxDB, and countless other systems that handle massive write throughput. Yet the fundamental insight remains surprisingly misunderstood: LSM-Trees don’t just “write faster”—they fundamentally restructure how data moves from memory to disk. ...

When Amazon engineers published the Dynamo paper in 2007, they revealed a technique that had been quietly powering some of the world’s largest distributed systems. The core idea—consistent hashing—originated from a 1997 MIT paper by David Karger and colleagues, but it took a decade before the industry fully embraced its elegance. Today, consistent hashing underpins Apache Cassandra, Amazon DynamoDB, Discord’s messaging infrastructure, Netflix’s content delivery network, and virtually every modern distributed database. The algorithm solves a deceptively simple problem: how do you distribute data across servers when those servers keep joining and leaving? ...