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Five signs you’ve outgrown Redis 3 Introduction Many firms find Redis easy to use when their data volumes and workloads are modest, but that changes quickly as their needs grow. High total cost of ownership (TCO), poor performance at scale, and operational complexity can lead to budget overruns, service level agreement (SLA) violations, and delayed application rollouts. … Five signs you’ve outgrown Redis 4 1. You need scalability and elasticity Having a scalable, elastic, real-time database is increasingly critical as data volumes grow and application demands evolve. Redis struggles on both counts, largely because it was initially designed as a single-instance, single-threaded system for in-memory caching. While recent releases and optional offerings provide some relief, Redis users still find themselves required … challenges. Although some automation of resharding is provided, the process still requires multiple steps from a system operator. ROF doesn’t solve Redis’ scalability problems because it keeps metadata and indexes in memory, caches “hot” data for performance, and relies on memory-hungry RocksDB processes behind the scenes. Speedb (a RocksDB-compatible engine) … loss. In this case, Redis falls short. Redis users often turn to Redis Sentinel or Redis Cluster to improve availability. The former monitors cluster status, alerting users if a primary node fails and assists with failover. However, Sentinel suffers from scalability issues: it’s not a clustering solution, all writes go to the master, and sharding isn’t supported. Although Redis Cluster is a clustering solution, it doesn’t have … server sprawl. Redis works well as a cache because of its in-memory performance, but users often complain of excessive DRAM consumption and inordinate growth in cluster size as data volumes increase. Built to work on commodity servers, Redis features a predominantly single-threaded design, so it cannot effectively support today’s modern multi-core processors. Furthermore,