Data modeling principles in Cassandra compel us to denormalize data as much as possible. Prior to Cassandra 3.0, the only way to query on a non-primary key column was to create a secondary index and query on it. However, secondary indexes have a performance trade-off if they contain high cardinality data. Often, high cardinality secondary indexes have to scan data on all the nodes and aggregate them to return the query results. This defeats the purpose of having a distributed system.
To avoid secondary indexes and client-side denormalization, Cassandra introduced the feature of materialized views, which does server side denormalization. You can create views for a base table and Cassandra ensures eventual consistency between ...
