How does replication affect performance?

Replication in Redis both helps and complicates performance, it all depends on which angle you look at: reads, writes, or the network.

#1. Reads, get faster

• Replicas can serve read-only requests, taking load off the master.

• With a lot of clients, the load can be split:

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  master → writes only replicas → reads only

• That scales the system horizontally and increases overall throughput.

The takeaway: replication significantly improves read performance.

#2. Writes, slow down slightly

• The master has to stream changes to every replica.
• That takes network resources and a bit of CPU time.
• With more replicas, load on the master grows proportionally to their number.

The takeaway: as the number of replicas grows, the master can slow down from distributing the data.

#3. The network, gets more loaded

• Every update travels over the network to every replica.
• If there's a lot of data (large keys, frequent writes), traffic can become noticeable.
• With cascading replication, some of that load can be redistributed.

The takeaway: the network is the main bottleneck when data volume is large.

#4. Latency between nodes

• Because of asynchrony, a replica can lag behind the master by fractions of a second or more.
• This doesn't affect the master's speed, but it reduces data consistency when reading from replicas.

#Summary:

Replication speeds up reads, slightly slows down writes, increases network load, but overall makes the system scalable and resilient. In Redis, it's optimized to keep the impact on the master's performance to a minimum.