Why Redis is fast, and Redis versus Memcached

Why it is fast

1. Everything lives in memory. No disk seek on the read path.
2. Simple, efficient data structures (hash tables, skip lists, compact encodings) with predictable costs.
3. A single-threaded event loop for command execution: no locks between threads, no context switching, and each command runs atomically. I/O multiplexing lets one thread serve thousands of connections.
4. A lean protocol and in-process memory management.

(Newer versions use extra threads for network I/O, but command execution stays ordered.)

Image: Mixabest · Public domain · Source · Wikimedia Commons: Dual-channel DDR memory use 6026

How the pieces fit

100%

Figure SDA-CORE-09-1 · Redis: event loop, memory, persistence and replication · © forcsguy.com

More than a cache

Redis stores typed values:

Type	Use
String	cached values, counters, flags
Hash	objects with fields (a user profile)
List	queues, recent items
Set	unique members, tags, set maths
Sorted set	leaderboards, priority queues, time-ordered data
Others	streams, bitmaps, HyperLogLog, geospatial

Because operations run on the server, you can increment, push, pop or intersect without a read-modify-write race.

100%

Figure SDA-CORE-09-2 · Redis data types and what they are for · © forcsguy.com

Durability options

Memory is volatile, so Redis offers:

• Snapshots (RDB): periodic point-in-time dumps. Compact, but recent writes can be lost.
• Append-only file (AOF): logs every write; replays on restart. Safer, bigger and a little slower.
• Or none at all when it is purely a cache.

Scaling and availability

• Replication: a primary copies to replicas (asynchronously), serving reads and enabling failover.
• Sentinel / managed failover promotes a replica when the primary dies.
• Cluster: splits keys across nodes by hash slot, for data larger than one machine.

Redis versus Memcached

	Redis	Memcached
Data types	many	strings only
Persistence	optional	none
Replication	yes	not built in
Threading	one for commands	multi-threaded
Best for	cache plus data structures, queues, counters	a very simple, large, pure cache

For most new projects Redis is the more flexible choice. Memcached remains fine for a straightforward cache that must use many CPU cores.

Pitfalls

• Memory is finite: set a maxmemory and an eviction policy (for example LRU).
• Avoid slow commands on huge collections.
• A very hot key still concentrates load on one node.

More on this site