System Design

MemcacheD vs Redis vs Aerospike — Which One to Choose for Your Application Design?

Memcached — Redis — Aerospike

Most Frequently Asked Design Interview Question — Choose As Per Your Use Case.

I've been asked this question multiple times in design interviews — Which cache architecture will you choose while designing high throughput and low latency applications that handle millions of requests per minute?

Sometimes interviewer asks about Persistence, Storage, Throughput and Replication, and Clustering comparison between these different Cache Types. One thing must be clear while designing a large-scale system that has throughput in multiple thousands per second, focus on what is needed for your application??? In this blog, we’ll mostly learn a comparison of these cache types and their use cases.

I’m listing a comprehensive comparison of MemcacheD, Redis, and Aerospike, highlighting their key differences:

What Are Different Data Types Supported?

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• MemcacheD: This supports simple key-value pairs (strings only).
• Redis: This supports various data types, including strings, hashes, lists, sets, sorted sets, bitmaps, hyperloglogs, and geospatial indexes.
• Aerospike: This primarily supports key-value storage with complex data types through collections and bins.

Who Provides Persistency if Server Restarts?

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• MemcacheD: This cache type does not support persistence; data is lost if the server restarts due to system failures.
• Redis: This offers multiple persistence options, such as RDB snapshots and AOF (Append-Only File) logs.
• Aerospike: This has strong durability features support for in-memory, SSD, and persistent storage with hybrid memory architectures.

Replication and Clustering — Why Not to Have It?

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• MemcacheD: This supports basic clustering with consistent hashing; but does not have built-in replication or automatic failover.
• Redis: This supports master-slave replication, automatic failover, and clustering for horizontal scalability.
• Aerospike: This is designed for high availability and scalability with strong support for replication and automatic failover, featuring a shared-nothing architecture.

Performance — Isn’t It a Major Consideration?

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• MemcacheD: This cache type is extremely fast for simple get and set operations, but limited to basic caching needs.
• Redis: This cache type is highly performant with low latency; and excels in scenarios requiring rapid read and write operations.
• Aerospike: This cache type is optimized for high-throughput and low-latency operations, especially with large datasets and mixed read/write workloads.

Memory Management —Shouldn't We Have It?

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• MemcacheD: This cache type uses a slab allocator to manage memory efficiently but has limited eviction policies.
• Redis: This cache type provides flexible eviction policies (e.g., LRU, LFU) and fine-grained control over memory usage.
• Aerospike: This cache type makes efficient use of memory and SSDs, with automatic data distribution and rebalancing across nodes.

Use Case — Which One Suits Where?

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• MemcacheD: Best for simple, high-performance caching where persistence and advanced data structures are unnecessary.
• Redis: Suitable for complex caching needs, real-time analytics, messaging, and other scenarios where data structures and persistence are important.
• Aerospike: Ideal for scenarios requiring extremely high performance, high availability, and scalability, such as fraud detection, recommendation engines, and real-time analytics.

In a Nutshell?

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MemcacheD: Choose MemcacheD for simple caching with a need for speed but no requirement for data persistence or advanced features.

Redis: Choose Redis if you need versatile data structures, persistence options, and real-time analytics capabilities with high performance.

Aerospike: Choose Aerospike for high-throughput, low-latency operations with large volumes of data, strong consistency, durability, and scalability features.

Each of these cache tools is suited for different use cases, and the choice between them should be based on our specific data handling, performance, and scalability requirements for building highly scalable distributed applications.

That’s all for this article. Hope you have enjoyed this article.

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