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Pros of Redis
Pros of Solr
  • 877
  • 535
    Super fast
  • 511
    Ease of use
  • 442
    In-memory cache
  • 321
    Advanced key-value cache
  • 190
    Open source
  • 179
    Easy to deploy
  • 163
  • 153
  • 120
  • 40
  • 39
    High Availability
  • 34
    Data Structures
  • 32
    Very Scalable
  • 23
  • 20
    Great community
  • 19
  • 17
    "NoSQL" key-value data store
  • 14
  • 12
  • 10
    Sorted Sets
  • 9
  • 8
    BSD licensed
  • 8
  • 7
    Async replication
  • 7
    Integrates super easy with Sidekiq for Rails background
  • 7
  • 6
    Open Source
  • 6
    Keys with a limited time-to-live
  • 5
  • 5
    Lua scripting
  • 4
    Awesomeness for Free!
  • 4
  • 3
    outstanding performance
  • 3
    Runs server side LUA
  • 3
  • 3
    LRU eviction of keys
  • 3
    Written in ANSI C
  • 3
    Feature Rich
  • 3
  • 2
    Data structure server
  • 2
    Performance & ease of use
  • 1
    Existing Laravel Integration
  • 1
    Automatic failover
  • 1
    Easy to use
  • 1
    Object [key/value] size each 500 MB
  • 1
  • 1
    Channels concept
  • 1
  • 1
    Temporarily kept on disk
  • 1
    Dont save data if no subscribers are found
  • 0
  • 35
  • 22
    Indexing and searching
  • 20
  • 19
  • 13
    Enterprise Ready
  • 5
  • 5
    Apache Software Foundation
  • 3
    Great Search engine
  • 2
    Security built-in

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Cons of Redis
Cons of Solr
  • 12
    Cannot query objects directly
  • 1
    No WAL
  • 1
    No secondary indexes for non-numeric data types
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    - No public GitHub repository available -

    What is 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.

    What is Solr?

    Solr is the popular, blazing fast open source enterprise search platform from the Apache Lucene project. Its major features include powerful full-text search, hit highlighting, faceted search, near real-time indexing, dynamic clustering, database integration, rich document (e.g., Word, PDF) handling, and geospatial search. Solr is highly reliable, scalable and fault tolerant, providing distributed indexing, replication and load-balanced querying, automated failover and recovery, centralized configuration and more. Solr powers the search and navigation features of many of the world's largest internet sites.

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    What companies use Redis?
    What companies use Solr?
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    Blog Posts

    Nov 20 2019 at 3:38AM


    Jun 6 2019 at 5:11PM


    What are some alternatives to Redis and Solr?
    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.
    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.
    RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
    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.
    Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
    See all alternatives
    Reviews of Redis and Solr
    Review of

    Redis is a good caching tool for a cluster, but our application had performance issues while using Aws Elasticache Redis since some page had 3000 cache hits per a page load and Redis just couldn't quickly process them all in once + latency and object deseialization time - page load took 8-9 seconds. We create a custom hybrid caching based on Redis and EhCache which worked great for our goals. Check it out on github, it's called HybriCache -

    How developers use Redis and Solr
    Cloudcraft uses

    Redis is used for storing all ephemeral (that's data you don't necessarily want to store permanently) user data, such as mapping of session IDs (stored in cookies) to current session variables at The many datastructures supported by Redis also makes it an excellent caching and realtime statistics layer. It doesn't hurt that the author, Antirez, is the nicest guy ever! These days, I would be really hard pressed to find any situation where I would pick something like Memcached over Redis.

    Trello uses

    Trello uses Redis for ephemeral data that needs to be shared between server processes but not persisted to disk. Things like the activity level of a session or a temporary OpenID key are stored in Redis, and the application is built to recover gracefully if any of these (or all of them) are lost. We run with allkeys-lru enabled and about five times as much space as its actual working set needs, so Redis automatically discards data that hasnโ€™t been accessed lately, and reconstructs it when necessary.

    Stack Exchange uses

    The UI has message inbox that is sent a message when you get a new badge, receive a message, significant event, etc. Done using WebSockets and is powered by redis. Redis has 2 slaves, SQL has 2 replicas, tag engine has 3 nodes, elastic has 3 nodes - any other service has high availability as well (and exists in both data centers).

    Brandon Adams uses

    Redis makes certain operations very easy. When I need a high-availability store, I typically look elsewhere, but for rapid development with the ability to land on your feet in prod, Redis is great. The available data types make it easy to build non-trivial indexes that would require complex queries in postgres.

    Kent Steiner uses

    I use Redis for cacheing, data storage, mining and augmentation, proprietary distributed event system for disparate apps and services to talk to each other, and more. Redis has some very useful native data types for tracking, slicing and dicing information.

    Kang Hyeon Ku uses

    elastic search ์™€ ํ•จ๊ป˜ ์œ ๋ช…ํ•œ ๊ฒ€์ƒ‰ ์—”์ง„ ์˜คํ”ˆ ์†Œ์Šค ์ค‘ ํ•˜๋‚˜ ์ด๋‹ค. ์ฒ˜์Œ ์„ค์ •ํ•  ๊ฒƒ์ด ๋งŽ์€๋ฐ, ์–ดํ”Œ๋ฆฌ์ผ€์ด์…˜์˜ ์ดํ•ด๊ฐ€ ์—†๋‹ค๋ฉด ์žฆ์€ ์ˆ˜์ •์ด ํ•„์š”ํ•˜๋‹ค. Solr Client ๋กœ ์ œ์–ด ํ•  ์ˆ˜ ์—†๊ณ  Server ์—์„œ ์„ค์ •ํ•ด ์ค˜์•ผํ•˜๋Š” ๊ฒƒ๋“ค์ด ์žˆ์–ด ์„œ๋ฒ„ ์„ค์ •ํ•˜๋Š” ๋ถ€๋ถ„์ด ์ค‘์š”ํ•˜๋‹ค. ์„œ๋ฒ„ ์„ค์ •๋งŒ ์ž˜ ๋˜์žˆ๋‹ค๋ฉด, Client ์ชฝ ์†Œ์Šค๋Š” ๋ณ„๊ฒŒ ์—†๋‹ค.

    ์ค‘์š”ํ•œ ๊ฑด ํ˜•ํƒœ์†Œ ๋ถ„์„๊ธฐ....

    The Independent uses

    Full text search is provided by a SOLR cluster. This is done on Master/Slave replication with Varnish as a cache.

    Blue Kangaroo uses

    Personalized search engine (for content-based filtering)

    Satoru Ishikawa uses

    ๆŸใƒ—ใƒญใƒ—ใƒฉใ‚คใ‚จใ‚ฟใƒชใชWebใ‚ขใƒ—ใƒชใ‚’ๅ‹•ใ‹ใ™ใฎใซๅฟ…่ฆใ ใฃใŸ(ใ‚คใƒณใ‚นใƒˆใƒผใƒซใจๆง‹็ฏ‰ใฎใฟ)

    SAP Hybris uses

    standard hybris-commerce implementation