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Memcached

5.8K
4.2K
+ 1
469
RocksDB

88
208
+ 1
11
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Memcached vs RocksDB: What are the differences?

Memcached: High-performance, distributed memory object caching system. Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering; RocksDB: Embeddable persistent key-value store for fast storage, developed and maintained by Facebook Database Engineering Team. RocksDB is an embeddable persistent key-value store for fast storage. RocksDB can also be the foundation for a client-server database but our current focus is on embedded workloads. RocksDB builds on LevelDB to be scalable to run on servers with many CPU cores, to efficiently use fast storage, to support IO-bound, in-memory and write-once workloads, and to be flexible to allow for innovation.

Memcached and RocksDB can be primarily classified as "Databases" tools.

"Fast object cache" is the primary reason why developers consider Memcached over the competitors, whereas "Very fast" was stated as the key factor in picking RocksDB.

Memcached and RocksDB are both open source tools. It seems that RocksDB with 14.1K GitHub stars and 3.09K forks on GitHub has more adoption than Memcached with 8.93K GitHub stars and 2.6K GitHub forks.

According to the StackShare community, Memcached has a broader approval, being mentioned in 750 company stacks & 264 developers stacks; compared to RocksDB, which is listed in 6 company stacks and 7 developer stacks.

Decisions about Memcached and RocksDB
 This was roughly 4 years ago at this point. We had been using an old iteration of memcache on Windows as the data cache per server for while and had for whatever reason opted to store our session data (to which the application is heavily dependent) in App Fabric. App Fabric had come to EOL and we needed to move away from it. As a quick search showed throughput capacity to be higher and overall features of Redis were better we initially implemented it. The number of changes required were minimal and we were able to migrate away to a more resilient system pretty quickly.
 We hit a snag in that the implementation of the Redis session handler at that point only took a single IP so we had to do use keepalived and HAProxy to display the application consistently between master and slave failovers. This caused issues on occasion of dropped connections to the backend service. We upgraded our client and could put both members into our config files and it stopped timing out. We were all happy in this and it was (for it's own part) a significant upgrade. Generally performance was better for all pages. 
 We found however, that our application was serializing all requests and locking on the thread via session lock for a great many things and this caused us and our users considerable headaches on occasion. We found that the implementation of the couchbase session handler gave us the option of ignoring session write locks and not be required to rewrite dozens of pages to handle the no session requirement as the application was working fine without the need to be threadsafe. Though the maximum throughput was not as good compared to Redis the application performance was considerably better as a result of the change. The multi-master write was a big benefit and the cross data center replication was a nice thing to have as that would allow our users to remain logged in even across DataCenter fail-over events (praying that never happened). Overall we used that for session handling and chose to use couchbase (in a 2nd cluster) to handle memcache requests as that gave us greater capacity to handle larger objects more efficiently. 
 We are, all these years later, looking to move into the newer features of couchbase to give us more and better use of this product that really has been the answer to a bunch of the growing pains we experienced. Since the decision performance has not been on wild rides and stability has never been better. So I sing the praises of couchbase to anyone that will listen.
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Pros of Memcached
Pros of RocksDB
  • 137
    Fast object cache
  • 128
    High-performance
  • 90
    Stable
  • 65
    Mature
  • 33
    Distributed caching system
  • 11
    Improved response time and throughput
  • 3
    Great for caching HTML
  • 2
    Putta
  • 5
    Very fast
  • 3
    Made by Facebook
  • 2
    Consistent performance
  • 1
    Ability to add logic to the database layer where needed

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Cons of Memcached
Cons of RocksDB
  • 2
    Only caches simple types
    Be the first to leave a con

    Sign up to add or upvote consMake informed product decisions

    What is Memcached?

    Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

    What is RocksDB?

    RocksDB is an embeddable persistent key-value store for fast storage. RocksDB can also be the foundation for a client-server database but our current focus is on embedded workloads. RocksDB builds on LevelDB to be scalable to run on servers with many CPU cores, to efficiently use fast storage, to support IO-bound, in-memory and write-once workloads, and to be flexible to allow for innovation.

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    What companies use Memcached?
    What companies use RocksDB?
    See which teams inside your own company are using Memcached or RocksDB.
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    What tools integrate with Memcached?
    What tools integrate with RocksDB?

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    Blog Posts

    Dec 22 2020 at 9:26PM

    Pinterest

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    RedisRubyKafka+9
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    GitHubDockerReact+17
    34
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    GitHubPythonReact+42
    47
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    GitHubPythonNode.js+47
    50
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    JavaScriptGitHubNode.js+26
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    What are some alternatives to Memcached and RocksDB?
    Redis
    Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets.
    Ehcache
    Ehcache is an open source, standards-based cache for boosting performance, offloading your database, and simplifying scalability. It's the most widely-used Java-based cache because it's robust, proven, and full-featured. Ehcache scales from in-process, with one or more nodes, all the way to mixed in-process/out-of-process configurations with terabyte-sized caches.
    Varnish
    Varnish Cache is a web application accelerator also known as a caching HTTP reverse proxy. You install it in front of any server that speaks HTTP and configure it to cache the contents. Varnish Cache is really, really fast. It typically speeds up delivery with a factor of 300 - 1000x, depending on your architecture.
    Hazelcast
    With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.
    MongoDB
    MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
    See all alternatives