Better Cassandra Indexes for a Better Data Model: Introducing Storage-Attached Indexing

DataStax has introduced Storage-Attached Indexing (SAI), a highly scalable, globally distributed index for Apache Cassandra®, now available on Astra and DataStax Enterprise (DSE). SAI enables developers to use relational WHERE patterns that leverage user-expected database indexing capabilities for Apache Cassandra. It provides an efficient and simpler filtering capability than Cassandra’s current indexing or bolt-on search solutions. SAI is deeply integrated with the storage engine of Apache Cassandra, which is why it's called Storage-Attached Indexing. It does not abstractly index tables but indexes Cassandra’s in memory Memtable and on-disk SSTable data structures as data is written. SAI intelligently filters results both in-memory and on-disk data structures at read time. SAI requires significantly lower disk usage compared to other native or bolt-on Cassandra index solutions, and it has been shown to improve performance for mutations (Cassandra insert, update, delete statements) by about 40% better throughput when using SAI compared to Secondary Indexes and about 230% better latency.