How to Manage Operational & Analytical Data at Massive Scale

It's probably not news to you, but handling the problem of data scalability – really handling it – hasn't been a trivial feat. You may have tried everything from buying more powerful hardware to creating overly complex and brittle data partitioning methods to using entirely new data storage and access models. These approaches may have helped in some regards, but they also came with some pretty big trade-offs. Enter distributed SQL. Over the years a lot of things have been deemed a “game-changer” – but distributed SQL actually deserves the moniker. Distributed SQL databases are relational databases engineered with a distributed architecture to scale out without any trade-offs. These databases retain standard SQL, ACID transactions and strong consistency while adding unprecedented levels of scalability. But that's only the tip of the iceberg. In this session, you'll: • Gain an understanding of the fundamental concepts of distributed SQL • Learn how MariaDB's distributed SQL implementation, Xpand, takes database elasticity, scale and high availability to the next level • Discover how you can use columnar indexing with distributed SQL to dramatically improve the execution speed of analytical queries on massive datasets