It delivers strong write-heavy performance with low latency. The main use cases for me are IoT and gaming. I also value its CQL compatibility, along with horizontal scalability and high availability.

I use ScyllaDB as the session store for my agent runtime, and it handles write-intensive traffic really well, which is essential for our agent swarm service as we need to write to the session store as the agent progresses. I like the strong availability ScyllaDB offers. Additionally, the natural partitioning based on the key aligns perfectly with my service's session ID and client's namespace as partition keys, which helps a lot. The initial setup on ScyllaDB Cloud was pretty easy.

I like ScyllaDB's ability to handle high throughput workloads while maintaining consistently low latency. The horizontal scalability makes it easy to accommodate increasing data volumes and traffic without major performance degradation. I appreciate ScyllaDB's low latency performance, which remains consistent even when workload and traffic increase. The shard per core architecture is a big advantage because it minimizes resource contention and allows the database to make efficient use of available CPU, memory, and storage. Additionally, I find the initial setup straightforward, as we used Docker Compose to set up a 3-node cluster across different physical nodes in the same network. ScyllaDB integrates well with our existing technology stack, helping us manage high-volume data workloads without significant changes to the application architecture.