本文有標(biāo)題黨之嫌。在NoSQL如日中天的今天，各種NoSQL產(chǎn)品可謂百花齊放，但每一個(gè)產(chǎn)品都有自己的特點(diǎn)，有長處也有不適合的場景。本文對(duì)Cassandra, Mongodb, CouchDB, Redis, Riak 以及 HBase 進(jìn)行了多方面的特點(diǎn)分析，希望看完此文的您能夠?qū)@些NoSQL產(chǎn)品的特性有所了解。 | | - Written in: Erlang
- Main point: DB consistency, ease of use
- License: Apache
- Protocol: HTTP/REST
- Bi-directional (!) replication,
- continuous or ad-hoc,
- with conflict detection,
- thus, master-master replication. (!)
- MVCC – write operations do not block 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 validation possible
- Authentication possible
- Real-time updates via _changes (!)
- Attachment handling
- thus, CouchApps (standalone js apps)
- jQuery library included
Best used: For accumulating, 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 an especially interesting feature, allowing easy multi-site deployments. | | | - Written in: C/C++
- Main point: Blazing fast
- License: BSD
- Protocol: 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 (good for rate limiting or statistics)
- Has sets (also union/diff/inter)
- Has lists (also a queue; blocking pop)
- Has hashes (objects of multiple fields)
- Of all these 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 data 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. | | | - 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 built-in
- Uses memory mapped files for data storage
- Performance over features
- After crash, it needs to repair tables
- Better durablity coming in V1.8
Best used: 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 example: For all things that you would do with MySQL or PostgreSQL, but having predefined columns really holds you back. | | | - Written in: Java
- Main point: Best of BigTable and Dynamo
- License: 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 reads (!)
- Map/reduce possible with Apache Hadoop
- I admit being a bit biased against it, because of the bloat and complexity it has partly because of Java (configuration, seeing exceptions, etc)
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 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. | | | - Written in: Erlang & C, some Javascript
- Main point: Fault tolerance
- License: Apache
- Protocol: HTTP/REST
- Tunable trade-offs for distribution and replication (N, R, 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 used: If you want something Cassandra-like (Dynamo-like), but no way you’re gonna deal with the bloat and complexity. If you need very good single-site scalability, availability and fault-tolerance, but you’re ready to pay for multi-site replication. 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)
- Modeled 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 source and sink modules
- Jruby-based (JIRB) shell
- No single point of failure
- Rolling restart for configuration changes and minor upgrades
- Random access performance is like MySQL
Best used: If you’re in love with BigTable.  And when you need random, realtime read/write access to your Big Data. For example: Facebook Messaging Database (more general example coming soon) | 原文鏈接：Cassandra vs MongoDB vs CouchDB vs Redis vs Riak vs HBase comparison
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