NoSQL比较:Cassandra vs MongoDB vs CouchDB vs Redis vs Riak vs HBase vs Membase vs Neo4j

红薯 发布于 2011/08/29 21:44
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本文详细介绍这几个 NoSQL 服务器的特点以及适用的场合!


  • 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. (Going away after 2.4!)
  • Master-slave replication
  • Simple values or hash tables by keys,
  • 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)
  • Sorted sets (high score table, good for range queries)
  • Redis has transactions (!)
  • Values can be set to expire (as in a cache)
  • Pub/Sub lets one implement messaging (!)

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 (auto failover with replica sets)
  • Sharding built-in
  • Queries are javascript expressions
  • Run arbitrary javascript functions server-side
  • Better update-in-place than CouchDB
  • Uses memory mapped files for data storage
  • Performance over features
  • Journaling (with --journal) is best turned on
  • On 32bit systems, limited to ~2.5Gb
  • An empty database takes up 192Mb
  • GridFS to store big data + metadata (not actually an FS)

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 most things that you would do with MySQL or PostgreSQL, but having predefined columns really holds you back.


  • Written in: Erlang & C, some Javascript
  • Main point: Fault tolerance
  • License: Apache
  • Protocol: HTTP/REST or custom binary
  • Tunable trade-offs for distribution and replication (N, R, W)
  • Pre- and post-commit hooks in JavaScript or Erlang, for validation and security.
  • Map/reduce in JavaScript or Erlang
  • Links & link walking: use it as a graph database
  • Indices: put metadata in, search it (coming in 1.0)
  • Large object support (Luwak)
  • Comes in "open source" and "enterprise" editions
  • Full-text search, indexing, querying with Riak Search server (beta)
  • Masterless multi-site replication replication and SNMP monitoring are commercially licensed

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. Could be used as a well-update-able web server.


  • Written in: Erlang & C
  • Main point: Memcache compatible, but with persistence and clustering
  • License: Apache 2.0
  • Protocol: memcached plus extensions
  • Very fast (200k+/sec) access of data by key
  • Persistence to disk
  • All nodes are identical (master-master replication)
  • Provides memcached-style in-memory caching buckets, too
  • Write de-duplication to reduce IO
  • Very nice cluster-management web GUI
  • Software upgrades without taking the DB offline
  • Connection proxy for connection pooling and multiplexing (Moxi)

Best used: Any application where low-latency data access, high concurrency support and high availability is a requirement.

For example: Low-latency use-cases like ad targeting or highly-concurrent web apps like online gaming (e.g. Zynga).


  • Written in: Java
  • Main point: Graph database - relationships
  • License: GPL, some features AGPL/commercial
  • Protocol: HTTP/REST (or embedding in Java)
  • Standalone, or embeddable into Java applications
  • Both vertices and edges can have metadata
  • Nice self-contained web admin
  • Advanced path-finding with multiple algorithms
  • Indexing of keys and relationships
  • Optimized for reads
  • Has transactions (in the Java API)
  • "Gremlin" graph traversal language
  • Scriptable in Groovy
  • Online backup, advanced monitoring and High Availability is AGPL/commercial licensed

Best used: For graph-style data. Neo4j is quite different from the others in this sense.

For example: Social relations, public transport links, road maps, network topologies.


  • 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.


(With the help of ghshephard)

  • 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)




@Rushmore : 实际上我既不懂NoSQL英文也很一般(看英文资料奇慢无比),而这个翻译过程既能熟悉一下技术又能提高英文水平(通过翻译最终达到不需要翻译)还对菜鸟有帮助,一石三鸟,何乐而不为?
@张金富 : 呵呵,我看到了,我只是说翻译起来辛苦而且很多情况下难免丢失语境,个人鄙见:coder真适应洋文 :)
@Rushmore : 没看到一楼求中文吗?翻译一下对入门者还是有帮助的。
@Rushmore : 就当练练手了
有点老的文档,那年redis还只是1.0,mongo还无replica set。这些技术特性文章其实也用不着翻译(辛苦)
mongodb暂时还没有无中心化的p2p式的架构。但是无schema限定是可以的。 btw,兄台关注的这两个特性都是很不错的特性!!!交个朋友吧~



  • 编写语言: C++
  • 亮点: 保留部分SQL语法特性 (查询, 索引)
  • 许可证: AGPL (Drivers: Apache)
  • 使用协议: 自定义, 二进制的(BSON)
  • 主/从表复制 (通过 replica sets 实现自动故障切换/故障转移)
  • 内置分区 
  • javascript 表达式查询 在服务端运行任意 javascript 函数
  • 比 CouchDB 更好的就地升级
  • 数据存储使用内存映射文件 
  • Performance over features (性能优于特性?
  • 通过添加 --journal 参数启动日志功能
  • 在32位系统上, 限制为2.5Gb
  • 每个空数据库占据 192Mb (现在好像没这么多了
  • 使用 GridFS 存储大数据和海量数据(非实际文件系统)

适用场合: 如果你需要动态查询. 如果你优先定义索引,而不是 map/reduce 函数. 如果你需要在大数据量上有良好的性能. 如果你本想使用 CouchDB, 但是你的数据变化过于频繁,填满硬盘.

例如: 大多数情况下, 你本想使用 MySQL 或者 PostgreSQL, 但是预先定义的列确确实实阻碍了你.



这里 有人翻译了 !
3. MongoDB
  • 所用语言:C++
  • 特点:保留了SQL一些友好的特性(查询,索引)。
  • 使用许可: AGPL(发起者: Apache)
  • 协议: Custom, binary( BSON)
  • Master/slave复制(支持自动错误恢复,使用 sets 复制)
  • 内建分片机制
  • 支持 javascript表达式查询
  • 可在服务器端执行任意的 javascript函数
  • update-in-place支持比CouchDB更好
  • 在数据存储时采用内存到文件映射
  • 对性能的关注超过对功能的要求
  • 建议最好打开日志功能(参数 --journal)
  • 在32位操作系统上,数据库大小限制在约2.5Gb
  • 空数据库大约占 192Mb
  • 采用 GridFS存储大数据或元数据(不是真正的文件系统)

最佳应用场景:适用于需要动态查询支持;需要使用索引而不是 map/reduce功能;需要对大数据库有性能要求;需要使用 CouchDB但因为数据改变太频繁而占满内存的应用程序。

例如:你本打算采用 MySQL或 PostgreSQL,但因为它们本身自带的预定义栏让你望而却步。