Redis VS memcached

Redis VS Memcached: Which one is the best overall

Developers must create high-performance and scalable web applications that provide lightning-fast user experiences in the digital landscape. To achieve this, they use in-memory database solutions such as Redis and Memcached, which are popular choices offering unique features and benefits.

In this article, we will compare Redis and Memcached in detail. We will discuss their features, performance, data structures, and use cases. We aim to help you decide which is best for your specific needs by presenting the strengths and weaknesses of each solution.

What is Redis?

Redis is an in-memory data structure store used as a database, cache, and message broker. It is open source and written in ANSI C. It supports multiple data types, including strings, hashes, lists, sets, sorted sets with range queries, bitmaps, and geospatial indexes with radius queries. Redis also provides various features, such as replication for high availability of the stored data across multiple nodes. Furthermore, it has built-in support for Lua scripting, allowing you to extend its feature set by creating custom commands or even entire applications within the server. Its high-performance capabilities and advanced features make it an ideal choice for applications needing real-time responses from their databases or fast access to large datasets stored in memory.

What is Memcached?

Memcached is an open-source, high-performance, distributed memory caching system. It’s designed to speed up dynamic web applications by temporarily storing and serving data stored in memory instead of from a database or file system. Memcached stores frequently requested data across multiple servers, providing fast access to the cached information when needed. This allows developers to reduce latency and improve application performance without changing their underlying codebase. With its easy setup process and low resource usage, Memcached is an excellent choice for any website looking for improved scalability and performance.

What Is Different About Redis VS Memcached?

Data Types

The first difference between Redis and Memcached is the data type. Memchache only store string data; wears Redis supports multiple data types.

What other data types are supported by Redis?

1. List

Redis Lists use a Linked List data structure to store unordered data and allow access by index. It is faster and provides consistent performance while adding or removing values from the start or end of a list compared to an Array data structure.

2. Hash

Hashes, also called dictionaries in some programming languages, enable storing closely related data in separate fields with their key-value pair relationships. They are similar to standard data structures in programming languages, but it’s important to note that there may not always be a 1:1 mapping. For instance, Redis’ version is quite “flat”, which means that a nested Python dictionary with different types of objects cannot be easily stored in a Redis Hash.

3. Set

Sets a type of collection that does not follow any specific order and contain unique items. With sets, you can add, remove, and check for the presence of members. One advantage of sets over lists is that they cannot have duplicate entries. Therefore, if you need to store a unique identifier, you can add it to a set and be certain that it does not already exist within the collection.

4. Sorted Set

Redis sorted sets are an extension of the Redis set that contains unique string elements. The distinction between them is that each element in the sorted set is assigned a score by Redis, which allows it to be sorted. Additionally, Redis sorted sets permit range access based on the assigned score.

Data Length

Another difference between Redis and Memcached is the data size. While Memcached limits its strings to 1 MB, Redis provides longer strings with a maximum size of 512 MB. Hence, using Redis is a better option if you storing bigger data.

Memory Usage

when you set the cache size and add data in Memcached, the daemon will gradually consume slightly more space than you specified. Recovering this extra space is impossible unless you restart the Memcached. Even if you delete all the keys or flush the database, the Memcached will still occupy the entire amount of memory that you configured it to use.

On the other hand, when setting a max size, Redis will never use more than it has to and will give you back memory it is no longer using. Redis provides configurable data eviction policies, allowing users to manage memory usage efficiently as data grows.

Disk I/O dumping

Memcached is designed primarily as a transient cache with no built-in disk storage or data persistence support. Consequently, it is well-suited for temporary data caching where data loss is tolerable, such as session storage or non-critical data caching. However, its lack of persistence makes it unsuitable for storing essential data that must survive server restarts or crashes.

On the other hand, Redis offers multiple options for data persistence, including snapshots (RDB) and append-only files (AOF). Snapshots periodically save the in-memory data to disk, while AOF logs every write operation to ensure data durability. These features make Redis a more versatile solution, capable of handling cases where data persistence is critical, such as caching user profiles or application settings.

Regarding disk storage, Redis’s strengths lie in its flexibility and support for data persistence, making it suitable for a wide range of applications that require data durability. In contrast, Memcached’s simplicity and lack of persistence make it ideal for scenarios where high-speed, temporary data storage is the primary concern.

When choosing between Memcached and Redis, it is essential to consider your application’s specific data persistence, durability, and memory management requirements to determine the most appropriate solution.


Memcached primarily scales through horizontal data partitioning (sharding) across multiple instances. Clients distribute the data using consistent hashing, which helps balance the load evenly and minimize data movement when adding or removing nodes. While this approach effectively scales read and write operations, it lacks built-in data redundancy and requires manual configuration and management. Additionally, Memcached’s simplicity limits its use to key-value data storage, making it less suitable for more complex scenarios.

Conversely, Redis offers several scaling options, including partitioning, replication, and clustering. Partitioning in Redis can be done similarly to Memcached by sharing data across multiple instances.

However, Redis also supports master-slave replication, where read operations can be offloaded to replica nodes, improving read scalability and data redundancy. Redis Cluster distributes data across multiple shards for a more comprehensive scaling solution, providing automatic failover and data replication. This feature ensures high availability and fault tolerance while maintaining ease of configuration.

It’s important to note that some Redis commands and data structures may not be fully compatible with clustering, which may require application-level adjustments.


Memcached and Redis have distinct replication processes, each with its features and best practices. Memcached, being a simple key-value cache, does not support native replication. Instead, it relies on client-side sharding or third-party solutions for data redundancy, which can lead to additional complexity and management overhead. Consequently, Memcached’s replication process is less robust and flexible than Redis’s.

On the other hand, Redis offers built-in master-slave replication, allowing users to create multiple replicas of the primary server to distribute read operations and increase data availability. This feature provides automatic failover, persistence options, and tunable consistency levels, making Redis more suitable for high-availability scenarios. Furthermore, Redis’s replication is asynchronous and supports partial resynchronization, which reduces the performance impact during synchronization events.

When comparing the two systems, it’s essential to consider these differences in their replication processes to make an informed decision based on data redundancy requirements, availability, and ease of configuration. Redis’s built-in replication capabilities offer a more comprehensive and flexible solution than Memcached’s reliance on external tools and techniques.


Memcached is inherently multi-threaded, simultaneously processing multiple incoming connections using different threads. This allows it to scale on multicore systems efficiently, providing high throughput and low latency under heavy load.

On the other hand, Redis is single-threaded by design, processing one command at a time. Single-threaded nature may lead to performance bottlenecks under high concurrency. To mitigate this, Redis offers asynchronous I/O with an event-driven architecture, and in version 6.0, it introduced threaded I/O that offloads tasks like networking and disk I/O to separate threads.

While Redis may not match Memcached’s raw performance in handling concurrent requests, its rich feature set and extensibility make it suitable for a broader range of use cases, including real-time analytics and messaging.


I would choose Redis over Memcached for several reasons. First and foremost, Redis offers richer data structures such as lists, sets, sorted sets, and hashes, while Memcached only supports simple key-value storage. This makes Redis more suitable for various applications, including real-time analytics, messaging systems, and caching.

Secondly, Redis provides built-in support for data persistence, which allows you to save the data stored in memory to disk periodically or on demand. This feature is essential in case of a server restart or crash, ensuring your data remains intact. On the other hand, Memcached is an in-memory caching system and does not offer data persistence, which can be a drawback for certain applications.

Another advantage of Redis is its support for transactions and atomic operations. This guarantees that multiple commands are executed sequentially without interruption, providing more consistency and reliability. Memcached lacks transaction support, making it less suitable for strict data consistency applications.

Lastly, Redis offers better scalability through its built-in support for master-slave replication. You can easily create multiple replicas of the primary server to distribute read operations, improving performance and fault tolerance. While Memcached can also be scaled horizontally, it requires manual configuration and does not have native support for replication.

In summary, Redis is a more versatile, feature-rich, and scalable solution than Memcached, making it the preferred choice for most applications.

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