【MongoDB】应用场景

24 Use Cases
24.1 适合场景
 Archiving and event logging
 归档和日志记录
 Document and Content Management Systems - as a document-oriented (JSON) database, MongoDB's flexible schemas are a good fit for this.
 文档和内存管理系统-作为面向文档数据库，mongodb的灵活的结构正适合这个
 ECommerce. Several sites are using MongoDB as the core of their ecommerce infrastructure (often in combination with an RDBMS for the final order processing and accounting).
 电子商务,采用mongoDB作为电子商务网站基础设施（通常联合关系型数据库处理订单流程和财务流程）
 Gaming. High performance small read/writes are a good fit for MongoDB; also for certain games geospatial indexes can be helpful.
 游戏.高性能的读/写正适合mongodb；而且对某些游戏来说，地理信息的索引也非常有用
 High volume problems. Problems where a traditional DBMS might be too expensive for the data in question. In many cases developers would traditionally write custom code to a filesystem instead using flat files or other methodologies.
 高容量问题.这种问题对关系型数据库来说花费很大，许多情况，开发者通常写入到文件系统
 Mobile. Specifically, the server-side infrastructure of mobile systems. Geospatial key here.
 移动通信.特别的，手机通信服务端的基础建设，比如地理空间信息
 Operational data store of a web site MongoDB is very good at real-time inserts, updates, and queries. Scalability and replication are provided which are necessary functions for large web sites' real-time data stores. Specific web use case examples:
 运营网站，mongoDB非常适合实时的插入更新和查询。可伸缩性和复制提供大型网站的实时数据的存储提供了保障。
 content management内存管理
 comment storage, management, voting 评论存储，管理和投票
 user registration, profile, session data 用户注册、简介、session数据
 Projects using iterative/agile development methodologies. Mongo's BSON data format makes it very easy to store and retrieve data in a document-style / "schemaless" format. Addition of new properties to existing objects is easy and does not generally require blocking "ALTER TABLE" style operations.
 项目采用迭代或者极限开发方式。MongoDB的BSON数据格式使存储和接收数据简单。
 Real-time stats/analytics
 实时状态分析
24.2 不适合场景
 Systems with a heavy emphasis on complex transactions such as banking systems and accounting. These systems typically require multi-object transactions, which MongoDB doesn't support. It's worth noting that, unlike many "NoSQL" solutions, MongoDB does support atomic operations on single documents. As documents can be rich entities; for many use cases, this is sufficient.
 需要复杂的事务支持的系统如银行系统，借贷系统等。这些系统需要多对象的事务，但是mongoDB不支持。值得注意的是，跟其他的NOSQL解决方法不同的是，MongoDB支持单文档的原子操作。由于文档能成为实体，对许多场景来说，这已足够了。
 Traditional Non-Realtime Data Warehousing. Traditional relational data warehouses and variants (columnar relational) are well suited for certain business intelligence problems – especially if you need SQL (see below) to use client tools (e.g. MicroStrategy) with the database. For cases where the analytics are realtime, the data very complicated to model in relationa, or where the data volume is huge, MongoDB may be a fit.
 传统的非实时的数据仓库。传统或者变种的关系型数据仓库非常适合于某些商业智能问题。特别是当你需要使用客户端工具操作数据库SQL的时候。当需要实时分析时，而且相对于关系型数据库数据模型复杂，或者数据容量很大，mongoDB非常实时
 Problems requiring SQL.
 需要SQL解决的问题。

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