Comparison of Cassandra, MongoDB, CouchDB, Redis, Riak, HBase

In NoSQL's heyday today, a variety of nosql products are blossoming, but each product has its own characteristics, there are advantages and not suitable for the scene. In this paper, the characteristics of cassandra, mongodb, couchdb, redis, riak  and  HBase  are analyzed in many aspects, I hope you will have a better understanding of the characteristics of these nosql products after reading this article.

CouchDB	written In: erlang Main point: db consistency, ease of use Li Cense: apache protocol: http/rest bi-directional (!) replication, continuous or AD-HOC, with conflict Detection, thus, master-master replication. (!) Mvcc–write operations do not blocks reads Previous versions of documents are available crash-only (reliable) design Needs Compacting from time to time views:embedded map/reduce formatting views:lists & shows Server-side document Validati On possible authentication possible real-time updates via _changes (!) Attachment Handling thus, couchapps  (standalone JS apps) JQuery library included Best Used: for Accumu lating, occasionally changing data, on which pre-defined queries-are to be run. Places where versioning is important. For EXAMPLE: CRM, CMS systems. Master-master replication is a especially interesting feature, allowing easy multi-site deployments.
Redis	written in: c/c++ Main point: blazing Fast License: bsd Pr Otocol: telnet-like disk-backed in-memory database, but since 2.0, it can swap to Disk. Master-slave replication simple keys and values, But complex operations like zrevrangebyscore INCR & Co (goo D for rate limiting or statistics) has sets (also Union/diff/inter) has lists (also a queue; blocking pop) has hashes (obj ECTs of multiple fields) of all this databases, only Redis does transactions (!) Values can be set to expire (as in a cache) Sorted sets (high score table, good for range queries) pub/sub and WATCH on da TA changes (!) Best used: for rapidly changing data with a foreseeable database size (should fit mostly in memory). For example: stock prices. Analytics. Real-time data collection. Real-time communication.
MongoDB	written in: c++ Main point: retains some friendly properties of SQL. (Query, index) LICENSE: AGPL (Drivers:apache) protocol: custom, Binary (bson) master/slave replication Queries are JavaScript expressions Run arbitrary javascript functions server-side Better update-in-place than CouchDB Sharding n Uses memory mapped files for data storage performance over features after crash, it needs to repair tables Better ity coming in V1.8 Best used: if for you need dynamic queries. If you are prefer to define indexes, not map/reduce functions. If you are need good performance on a big DB. If you are wanted CouchDB, but your data changes much, too up filling. For example: for all things so you would does with MySQL or PostgreSQL, but have predefined columns Holds you.
Cassandra	written In: java Main point: best of BigTable and Dynamo Li Cense: apache protocol: custom, Binary (Thrift) tunable trade-offs for distribution and replication (n, r ,  w) Querying by column, range of keys bigtable-like features:columns, column families writes are much faster than R EADS (!) Map/reduce possible with Apache Hadoop I admit being a bit biased against it, because of the bloat and complexity it has p artly because of Java (configuration, seeing exceptions, etc) Best Used: when You write more than you read (Loggi NG). If every component of the system must is in Java. ("No one gets fired for choosing Apache ' s stuff.") For example: banking, financial industry (though not necessarily for financial transactions, but Ries are much bigger than that.) Writes are faster than reads, so one natural niche are real time data analysis.
Riak	written In: erlang & C, some Javascript Main point: fault to Lerance License: apache protocol: http/rest tunable trade-offs for distribution and replication (N, R,& nbsp W) Pre-and Post-commit hooks, for validation and security. Built-in Full-text search map/reduce in JavaScript or Erlang comes in ' open source ' and ' Enterprise ' editions Best use D: if you want something Cassandra-like (dynamo-like), but no way your ' re gonna deal with the bloat and complexity. If you are need very good single-site scalability, availability and fault-tolerance, but you ' re ready to pay for multi-site re Plication. for Example: point-of-sales data collection. Factory control systems. Places where even seconds of downtime hurt.
HBase	Written In:java Main point:billions of rows X millions of columns License:apache protocol:http/rest (also Thrift) Mode Led after BigTable map/reduce with Hadoop Query predicate push down via server side scan and get filters optimizations for Real time queries A High performance Thrift Gateway HTTP supports XML, protobuf, and binary cascading, hive, and pig sour CE and sink modules jruby-based (JIRB) Shell No single point of failure rolling restart for configuration changes and Mino R Upgrades Random Access performance is like MySQL Best Used:if you ' re in love with BigTable. Need random, realtime Read/write access to your The big Data. For Example:facebook messaging Database (more general example coming soon)

Original link: Cassandra vs MongoDB vs CouchDB vs Redis vs Riak vs HBase comparison