Apache Cassandra is a scalable database with high availability features. But they come with severe limitations in term of querying capabilities. Since the introduction of SASI in Cassandra 3.4, the limitations belong to the pass. Now you can create performant indices on your columns as well as benefit from **full text search** capabilities with the introduction of the new `LIKE %term%` syntax. To illustrate how SASI works, we'll use a database of 100 000 albums and artists. We'll also show how SASI can help to accelerate analytics scenarios with Spark using SparkSQL predicate-pushdown