scylladb

Inside Medium’s move from relational features to list features in its ScyllaDB-based feature store “Keep readers reading” is the not-so-simple goal of Medium’s recommendations system. To predict what’s most likely to appeal to a particular reader at any given time, Medium continuously processes user activity signals (stories read, recommendations shown, follows, likes, etc.).

Welcome to the latest installment of a new blog series introducing some of the experts you might encounter when you work with ScyllaDB. (Past ones: Tyler Denton, Faisal Saeed). Today we’re featuring Susie Solis, Technical Support Engineer on the Customer Experience team here at ScyllaDB. She lives in Colorado and has been at ScyllaDB for almost 3 years. Let’s learn a little abou...

Martin Kleppmann and Chris Ricommini’s scalability considerations for designing data-intensive applications The following is an excerpt from Chapter 2 of the shiny new Designing Data-Intensive Applications Second Edition, by Martin Kleppmann and Chris Riccomini. It is published here with permission from O’Reilly. For more background on the book (known as the bible of data system...

Discover the strategies, challenges, and trade-offs teams faced in a few real-world migrations to ScyllaDB In “What Matters Most for NoSQL Migrations”, I shared my top strategies for planning, executing and de-risking a NoSQL database migration. I discussed key steps like schema and data migration, data validation and important considerations such as technology switches, tooling...

We moved I/O off application cores to dedicated cores to give compute-heavy workloads more breathing room Modern high-throughput systems often run on machines with many cores. At that scale, one practical problem becomes increasingly visible: CPU time spent on low-level I/O handling competes directly with CPU time needed for application-level work. In this post, we explore how s...