Read-heavy pattern

In an IoT application with Cassandra as the data store, if the number of reads is higher when compared to the writes, the read consistency levels should not be set high. Consistency levels of LOCAL_ONE, ONE are ideal. In this case, the data store works like a source. In this situation, if the read consistency levels are set high, then the clients will have to wait for each read until the read is completed successfully from the required number of nodes as per the consistency level setting. The complexity increases when there are Cassandra clusters spread across multiple data centers. When the clients wait for the read to complete because of high consistency level settings, the availability will be less and the efficiency to complete the reads will also decrease. This, in turn, increases the latency, and the overall application performance will be affected. It is also ideal to have secondary indexes in the Cassandra column families where a huge number of reads are taking...