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Redis: concurrency latency issues.

Issue 1.)

Redis Hash tables are O(1) average and amortized case complexity.
Redis suffers from O(n) worst-case time complexity because of Hash Collisions which cause rehashing issue realtime applications and applications that need low latency should not use Redis hash table as their data structure.

Issue 2.)

Redis is Single Threaded : one process serves requests from all clients.
As the number of clients grows, the percentage of resource time given to each client decreases and each client spends an increasing amount of time waiting for their share of Redis server time.

Redis vs. Cassandra

On Issue 1.)

Cassandra using B-Tree data structure that is distributed among many servers implementing durable log writes, therefore, Cassandra does not suffer from Hash Collisions like Redis.

On Issue 2.)

Cassandra is multi-threaded, multi server distributed database using B-Tree data structure. Hundreds of thousands of records can be ingested concurently by any node in Cassandra cluster.