Apache Cassandra and ScyllaDB are distributed databases designed to handle massive globally-distributed workloads. They were both created with a highly scalable architecture and both use the same CQL query language. But their priorities and design decisions have diverged quite a bit over the past decade.
From the start, there have been notable differences in fundamentals such as sharding, caching, and indexing. The differences have become more significant with the most recent releases – especially with scaling, efficiency, and support for real-time AI workloads.
Join Guilherme Nogueira, ScyllaDB Technical Director, for a live 25-min the technical differences and what they mean for different types of high-performance database workloads.
We’ll cover:
- A look inside each database’s architecture and internal operations
- How performance, features, and deployment options compare
- What’s unique in each and what use cases / technical requirements benefit most from each database’s differentiators
