Nowadays applications move very fast having new features every now and then. Software needs to process more and more data. So there is a need for alternatives to SQL databases, where we are not linked to a fixed database schema; where the amount of data will not reduce the performances. For all these reasons, NoSQL started to make it's way. And it's now part of the backend of most big websites like Facebook or Twitter.
With SQL you can almost switch from one database vendor to another with little to no effort thanks to SQL standard. With NoSQL databases there is no standard way to access these databases, so you need to consider twice your choice to make sure you will go for the solution that best fit your needs and not have to start all over your integration in a few months.
This comparison is inspired from Kristof Kovacs article:
http://kkovacs.eu/cassandra-vs-mongodb-vs-couchdb-vs-redis
Cassandra | CouchDB | Clusterpoint | DocumentDB | DynamoDB | HBase | MongoDB | Redis | |
---|---|---|---|---|---|---|---|---|
Best used | When you write more than you read (logging). If every component of the system must be in Java. ("No one gets fired for choosing Apache's stuff.") | For accumulating, occasionally changing data, on which pre-defined queries are to be run. Places where versioning is important. | Primarily offered as Database as a Service, allows you to operate 50-node cluster at a fraction of a cost (Pay per CPU). Most suitable for Web-based ACID-compliant solutions, but can be used for many other tasks. | When you have a lot of simple records. | If you're in love with BigTable. :) And when you need random, realtime read/write access to your Big Data. | If you need dynamic queries. If you prefer to define indexes, not map/reduce functions. If you need good performance on a big DB. If you wanted CouchDB, but your data changes too much, filling up disks. | For rapidly changing data with a foreseeable database size (should fit mostly in memory) | |
Usage example | Banking, financial industry (though not necessarily for financial transactions, but these industries are much bigger than that.) Writes are faster than reads, so one natural niche is real time data analysis. | CRM, CMS systems. Master-master replication is an especially interesting feature, allowing easy multi-site deployments. | Feature-wise sits between SQL and MongoDB offering great horizontal scaling in combination with transaction support, Geo, Full-text searches, group-by. | Facebook Messaging Database | For all things that you would do with MySQL or PostgreSQL, but having predefined columns really holds you back. | Stock prices. Analytics. Real-time data collection. Real-time communication. | ||
Known Shortcomings | Lacks embedded language. | No ordering. | No embedded language. Multiple index queries. Lacks features. | Sizes limited by amount of RAM. | ||||
Main focus | Best of BigTable and Dynamo | DB consistency, ease of use | Simple setup. Features. Horizontal scaling. | Billions of rows X millions of columns | Retains some friendly properties of SQL. (Query, index) | Speed | ||
License | Apache | Apache | Proprietary, but available as free download. | Proprietary. Cloud-only. | Proprietary. Cloud-only. | Apache | AGPL (Drivers: Apache) | BSD |
Pricing | Free download or pay per resource (CPU, Traffic, Storage) | Pay per requests / traffic. | Free download or Pay per instance + Service (MongoLab) | |||||
Projects using it |
| http://wiki.apache.org/couchdb/CouchDB_in_the_wild |
http://wiki.apache.org/hadoop/Hbase/PoweredBy |
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Technical details | ||||||||
Latest version | 2.1.4 | 1.6.1 | 3.0 | 0.98.4 | 3.0.3 | 6.0.4 | ||
Release date | 2015-04-01 | 2014-09-03 | 2015-02-15 | 2014-07-21 | 2015-05-12 | 2020-05-28 | ||
Initial release | 2008 | 2005 | 2006 | 2012 | 2009 | 2009 | ||
Consistency | Strong | Strong/Eventual | Eventual (strong with flag) | |||||
Replication | Multi-master replication | Multi-master | Master/slave | Master/slave | ||||
Protocol | Thrift (Binary) | HTTP/REST | HTTP/Rest | REST | HTTP/REST (and Thrift) | BSON (Binary) | Telnet-like | |
Data Presentation | XML / JSON | JSON | JSON | JSON | ||||
Development language | Java | Erlang | C++ | Java | C++ | C/C++ | ||
Platforms | Cross-platform | Cross-platform | Cloud or Linux | Cloud only | Cloud only "DynamoDB Local" cross-platform (single instance for development) | Cross-platform | Cross-platform | Cross-platform |
API Language | ||||||||
Embedded Language | None | JavaScript | None | JavaScript | None | |||
Additional | ||||||||
Website | http://cassandra.apache.org/ | http://couchdb.apache.org/ | http://clusterpoint.com/ | http://azure.microsoft.com/en-us/services/documentdb/ | http://aws.amazon.com/dynamodb/ | http://hbase.apache.org/ | http://www.mongodb.org/ | http://redis.io/ |
Wikipedia | http://en.wikipedia.org/wiki/Cassandra_(database) | http://en.wikipedia.org/wiki/CouchDB | http://en.wikipedia.org/wiki/Clusterpoint | http://en.wikipedia.org/wiki/DocumentDB | http://en.wikipedia.org/wiki/Amazon_DynamoDB | http://en.wikipedia.org/wiki/Hbase | http://en.wikipedia.org/wiki/MongoDB | http://en.wikipedia.org/wiki/Redis_(data_store) |
Additional link | http://justazure.com/mongodb-vs-azure-documentdb/ | http://wiki.apache.org/hadoop/Hbase | ||||||
Features | ||||||||
Cloud DB | Yes | Yes | Yes | Third Party | ||||
Transaction support | No | No | Yes | No | No | No | No | Yes |
Domain-model Aggregation | Yes | No | No | Yes | ||||
GeoSpatial | Yes | No | Yes | Yes | ||||
FullText | Yes | No | No | |||||
Commercial Support | Included into DB-Service | Third parties. |
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