Redis and Memcached are both in-memory data stores commonly used for caching. They’re often mentioned in the same breath, but they’ve evolved to serve somewhat different purposes. Understanding those differences helps you choose the right tool—and avoid using a sledgehammer when a simple hammer would suffice.
The Quick Answer
Choose Redis if: You need data structures beyond simple key-value pairs, persistence, replication, pub/sub messaging, or Lua scripting. Redis is the more versatile option with broader capabilities.
Choose Memcached if: You need a simple, fast cache for string values and want the most straightforward operational model. Memcached does one thing and does it well.
Either works if: You’re building a basic caching layer for database query results or session storage and don’t need Redis’s advanced features.
What Memcached Does
Memcached is a distributed memory caching system. It stores key-value pairs in memory across multiple servers, providing fast access to frequently requested data. That’s it—and that simplicity is its strength.
You give Memcached a key and a value (a string or serialized object). You get it back by key. Values expire after a configurable time. When memory fills up, Memcached evicts the least recently used items. There’s no persistence, no replication, no complex data structures.
This simplicity translates to predictable performance, easy operations, and minimal overhead. Memcached excels at being a cache—a temporary store that speeds up access to data that’s expensive to compute or retrieve.
What Redis Does
Redis started as a data structure server—an in-memory store that supports strings, lists, sets, sorted sets, hashes, bitmaps, hyperloglogs, and streams. It has evolved into a multi-purpose tool that can function as a cache, message broker, and even a primary database for certain use cases.
Redis offers optional persistence (snapshots and append-only files), replication for high availability, Lua scripting for atomic operations, pub/sub messaging, and transactions. It’s far more capable than Memcached, which also means it’s more complex.
Where Memcached Excels
Simple Caching
For basic caching—store a value, retrieve it by key, let it expire—Memcached is hard to beat. It’s fast, simple, and does exactly what you need without extra complexity. If your caching needs are straightforward, Memcached’s simplicity is an advantage.
Multi-Threaded Performance
Memcached is multi-threaded, meaning a single instance can utilize multiple CPU cores. For workloads that would saturate a single-threaded process, Memcached can handle more throughput per instance. This matters for extremely high-volume caching scenarios.
Memory Efficiency for Simple Values
Memcached has lower memory overhead per key for simple string values. When you’re caching millions of small values, this efficiency difference can add up. If memory utilization is critical and your data model is simple, Memcached uses memory more efficiently.
Predictable Performance
Memcached’s limited feature set means fewer surprises. There’s no persistence impacting latency, no complex commands with varying time complexity. Performance characteristics are predictable and consistent.
Operational Simplicity
There’s less to configure, monitor, and understand with Memcached. For teams that want a cache without learning a new system, Memcached’s minimal feature set reduces cognitive overhead.
Where Redis Excels
Data Structures
Redis’s rich data structures enable use cases beyond simple caching:
- Lists: Implement queues, recent activity feeds, or bounded collections
- Sets: Track unique items, compute intersections and unions efficiently
- Sorted Sets: Build leaderboards, priority queues, or time-series indices
- Hashes: Store objects with individual field access without serialization overhead
- Streams: Build event logs and message queues with consumer groups
These data structures let you solve problems that would require multiple round trips or application-side logic with Memcached.
Persistence Options
Redis can persist data to disk through RDB snapshots or AOF (Append Only File) logs. This means Redis can survive restarts without losing all cached data. For caches where cold-start performance matters, persistence provides a warm cache after restarts.
Persistence also enables using Redis as a primary data store for certain use cases—session storage, feature flags, rate limiting—where data loss would be problematic but a full database is overkill.
Replication and High Availability
Redis supports master-replica replication and, with Redis Sentinel or Redis Cluster, automatic failover. For applications that can’t tolerate cache unavailability, Redis provides high-availability options that Memcached lacks natively.
Pub/Sub Messaging
Redis includes publish/subscribe messaging capabilities. While not a replacement for dedicated message brokers, Redis pub/sub works well for real-time notifications, cache invalidation broadcasts, and simple event distribution.
Atomic Operations and Lua Scripting
Redis operations are atomic, and Lua scripts can perform complex logic atomically on the server. This enables patterns like distributed locks, rate limiting with complex rules, and compare-and-set operations that would be error-prone with non-atomic operations.
Single-Threaded Predictability
Redis’s single-threaded model (for command processing) means no locking overhead and predictable execution. Commands execute sequentially, making reasoning about behavior straightforward. Redis 6+ added I/O threading for network operations while keeping command execution single-threaded.
Performance Comparison
For simple get/set operations, both systems perform similarly—sub-millisecond latency with proper network configuration. The performance difference rarely matters for typical caching workloads.
Memcached advantages:
- Multi-threaded can utilize more CPU per instance
- Slightly lower latency for simple operations in some benchmarks
- More efficient memory usage for simple string values
Redis advantages:
- Complex operations (data structure commands) execute server-side
- Pipelining and transactions reduce round trips
- Lua scripting avoids network overhead for complex logic
In practice, network latency often dominates. A nearby cache is fast regardless of whether it’s Redis or Memcached. Optimization efforts are usually better spent on cache hit rates than microseconds of per-operation latency.
Scaling Patterns
Memcached scaling is straightforward: add more servers, distribute keys using consistent hashing on the client side. Clients are responsible for distributing and locating data. This model scales horizontally without coordination between Memcached instances.
Redis scaling has multiple options:
- Single instance: Works for moderate workloads
- Replication: Read replicas for read-heavy workloads
- Redis Cluster: Automatic sharding across multiple nodes
- Client-side sharding: Similar to Memcached’s model
Redis Cluster adds complexity but provides automatic failover and resharding. For large-scale deployments, this coordination has value but requires more operational expertise.
When to Choose Memcached
- Your use case is straightforward caching of serialized objects or strings
- You want the simplest possible operational model
- Memory efficiency for simple values is important
- You need multi-threaded performance on individual instances
- You have existing Memcached expertise and infrastructure
When to Choose Redis
- You need data structures beyond simple key-value pairs
- Persistence matters—you want cache data to survive restarts
- You need replication and high availability
- You want pub/sub messaging capabilities
- You need atomic operations or Lua scripting
- You might use the cache as a primary store for some data
The “Just Use Redis” Argument
Many teams default to Redis because it can do everything Memcached does plus more. This is a reasonable position—Redis handles simple caching perfectly well, and having additional capabilities available doesn’t hurt.
The counterargument is that unnecessary complexity has costs. Memcached’s simplicity means fewer configuration options to get wrong, fewer features to misuse, and less to learn. For teams that genuinely only need simple caching, Memcached’s constraints can be beneficial.
That said, the operational difference has narrowed. Managed Redis services (Amazon ElastiCache, Redis Cloud, Azure Cache for Redis) reduce the complexity of running Redis. If you’re using a managed service, the operational simplicity argument for Memcached is less compelling.
Managed Services
Both systems have excellent managed offerings:
Amazon ElastiCache supports both Redis and Memcached. You get the same API with AWS handling infrastructure management.
Redis Cloud (from Redis Inc.) provides managed Redis with additional enterprise features.
Azure Cache for Redis and Google Cloud Memorystore offer managed Redis.
Managed services reduce the operational differences between the systems. When infrastructure management isn’t your burden, the choice focuses more on features and less on operations.
Common Use Cases
Session storage: Redis’s persistence and data structures make it slightly better for sessions. Memcached works but risks session loss on restarts.
Database query caching: Both work well. Choose based on other requirements.
Page/fragment caching: Both work well. Memcached’s simplicity is sufficient.
Leaderboards and counters: Redis’s sorted sets and atomic increments are purpose-built for this.
Rate limiting: Redis’s atomic operations and expiration make it well-suited. Memcached can work but requires more careful implementation.
Distributed locks: Redis’s atomic operations and Lua scripting enable reliable distributed locking. Memcached isn’t designed for this.
Message queues: Redis lists and streams provide queue capabilities. Memcached doesn’t support this use case.
The Bottom Line
For pure caching needs, either Redis or Memcached will serve you well. Memcached offers simplicity; Redis offers versatility. The choice often comes down to whether you need Redis’s additional capabilities.
If you’re unsure, Redis is the safer default—it handles simple caching effectively while providing room to grow into more sophisticated use cases. But don’t dismiss Memcached’s elegant simplicity. Sometimes the tool that does one thing well is exactly what you need.