If you were forced to choose just one thing that would prompt you to move your mission-critical functionality to a new database, what would it be? Better performance? Worries about future scaling on your existing platform? Easier time for your DevOps? What about awesome support from the company itself? At Scylla Summit 2017, mParticle’s Nayden Kolev explained how all of the above factors started the group one year ago on a fruitful collaboration with Scylla in production.
Solving your performance problems with Intel Optane Organizations often face problems with their current database infrastructure regarding performance, data persistence, and cost. Some may use in-memory databases to help address performance concerns but they may run into data persistence issues. Sacrificing the integrity of your data is never a good tradeoff for performance. Also, more memory in a server will drive up costs. An ideal solution would provide the performance of an in-memory database without compromises on throughput, latency, and data persistence.
How do you quantify how effective your database system is in terms of throughput, latency and CPU usage? And what do you do when there is a risk to your SLA? These were the main questions explored in Lukasz Pachiarek and Szymon Szymanski of Allegro’s talk at Scylla Summit 2017.
At ScyllaDB, our development team is all about performance with improved latency and throughput. Our speakers at our recent Scylla Summit provided many tips and tricks to make Scylla’s superior latency and performance even better. ScyllaDB’s VP of R&D, Schlomi Livne, added to the growing repertoire of these tips with his talk Planning your queries for maximum performance. In it, he outlined some of the how and why of Scylla performance, and concluded with seven rules to optimize your queries.