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Memcached

6.7K
4.9K
+ 1
470
RocksDB

103
257
+ 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.

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Pros of Memcached
Pros of RocksDB
  • 138
    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

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    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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    Jobs that mention Memcached and RocksDB as a desired skillset
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    What tools integrate with Memcached?
    What tools integrate with RocksDB?

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    Blog Posts

    Jan 26 2022 at 4:34AM

    Pinterest

    Amazon EC2RocksDBOpenTSDB+3
    3
    688
    Dec 22 2020 at 9:26PM

    Pinterest

    Amazon EC2MemcachedC lang+4
    10
    2483
    Jun 6 2019 at 5:11PM

    AppSignal

    RedisRubyKafka+9
    15
    1273
    GitHubDockerReact+17
    35
    33682
    What are some alternatives to Memcached and RocksDB?
    Redis
    Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
    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