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Learn MorePros of Redis
Pros of Solr
Pros of Redis
- Performance875
- Super fast535
- Ease of use511
- In-memory cache441
- Advanced key-value cache321
- Open source190
- Easy to deploy179
- Stable163
- Free153
- Fast120
- High-Performance40
- High Availability39
- Data Structures34
- Very Scalable32
- Replication23
- Great community20
- Pub/Sub19
- "NoSQL" key-value data store17
- Hashes14
- Sets12
- Sorted Sets10
- Lists9
- BSD licensed8
- NoSQL8
- Async replication7
- Integrates super easy with Sidekiq for Rails background7
- Bitmaps7
- Open Source6
- Keys with a limited time-to-live6
- Strings5
- Lua scripting5
- Awesomeness for Free!4
- Hyperloglogs4
- outstanding performance3
- Runs server side LUA3
- Networked3
- LRU eviction of keys3
- Written in ANSI C3
- Feature Rich3
- Transactions3
- Data structure server2
- Performance & ease of use2
- Existing Laravel Integration1
- Automatic failover1
- Easy to use1
- Object [key/value] size each 500 MB1
- Simple1
- Channels concept1
- Scalable1
- Temporarily kept on disk1
- Dont save data if no subscribers are found1
- Jk0
Pros of Solr
- Powerful35
- Indexing and searching22
- Scalable20
- Customizable19
- Enterprise Ready13
- Apache Software Foundation5
- Restful5
- Great Search engine4
- Security built-in2
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Cons of Redis
Cons of Solr
Cons of Redis
- Cannot query objects directly14
- No secondary indexes for non-numeric data types2
- No WAL1
Cons of Solr
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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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What tools integrate with Redis?
What tools integrate with Solr?
What tools integrate with Redis?
What tools integrate with Solr?
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What are some alternatives to Redis and Solr?
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.
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.
RabbitMQ
RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
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.
Cassandra
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.