Final answer:
It is true that Cassandra supports joins when used with Apache Spark, which is proficient in handling big data analytics and can efficiently perform join operations on large datasets.
Step-by-step explanation:
The statement that Cassandra supports joining while working in conjunction with Spark is true. Apache Cassandra is a NoSQL database known for its scalability and high availability without compromising performance. Linear scalability and proven fault-tolerance make it the perfect platform for mission-critical data. Cassandra's storage model is designed to be distributed and does not natively support the relational join operation. However, Apache Spark is a powerful, open-source processing engine for big data and it pairs well with Cassandra. Spark can perform complex data analytics, which includes joining tables from Cassandra or from different data sources. Spark's ability to process large datasets at high speeds allows it to handle joins efficiently, even with the large datasets typically stored in Cassandra databases.