It was designed to be compatible with Apache Cassandra while achieving significantly higher throughputs and lower latencies.

It supports the same protocols as Cassandra (CQL) and the same file formats (SSTable), but is a completely rewritten implementation, using the C++20 language replacing Cassandra's Java, and the Seastar[1] asynchronous programming library replacing classic Linux programming techniques such as threads, shared memory and mapped files.

[2] ScyllaDB uses a sharded design on each node, meaning that each CPU core handles a different subset of data.

[4] Independent testing has not always been able to confirm such 10-fold throughput improvements, and sometimes measured smaller speedups, such as 2x.

[5] A 2017 benchmark from Samsung observed the 10x speedup on high-end machines – the Samsung benchmark reported that ScyllaDB outperformed Cassandra on a cluster of 24-core machines by a margin of 10–37x depending on the YCSB workload.