sns架构讨论

nosql    tokyocabint   mongodb

异步队列httpsqs、gearman、message queue、starling（被Kestrel替代） ，Kestrel（memcache），  ActiveMQ，ZeroMQ，

 RabbitMQ （amqp）

activemq（jms）被 Apollo替代  支持mysql持久化 消息队列使用

0MQ (ZeroMQ) 是一个轻量级消息内核。它实现了30微秒的端到端延迟和每秒超过300万的信息。它可用于C、C++、Python、.NET /Mono、Fortran和Java语言。它运行在AIX ， FreeBSD的，基于HP - UX ， Linux和MacOS下， OpenBSD系统， OpenVMS ， QNX Neutrino， Solaris和Windows操作系统。

memcached(memcached1.4.5)

 

 

搜索  sphinx luncene
图片是fastdfs（类似google的hadoop的dfs）

 

lvs，memcachedb

 

 

Message Queue Servers

Message queue servers are available in various languages, Erlang (RabbitMQ), C (beanstalkd), Ruby (Starling or Sparrow), Scala (Kestrel, Kafka) or Java (ActiveMQ). A short overview can be found here

Sparrow

• written by Alex MacCaw
• Sparrow is a lightweight queue written in Ruby that “speaks memcache”

Starling

• written by Blaine Cook at Twitter
• Starling is a Message Queue Server based on MemCached
• written in Ruby
• stores jobs in memory (message queue)
• documentation: some good tutorials, for example the railscast about starling and workling or this blog post about starling

Kestrel

• written by Robey Pointer
• Starling clone written in Scala (a port of Starling from Ruby to Scala)
• Queues are stored in memory, but logged on disk

RabbitMQ

• RabbitMQ is a Message Queue Server in Erlang
• stores jobs in memory (message queue)

Apache ActiveMQ

• ActiveMQ is an open source message broker in Java

Beanstalkd

• written by Philotic, Inc. to improve the response time of a Facebook application
• in-memory workqueue service mostly written in C
• Docu: http://nubyonrails.com/articles/about-this-blog-beanstalk-messaging-queue

Amazon SQS

• Amazon Simple Queue Service

Kafka

• Written at LinkedIn in Scala
• Used by LinkedIn to offload processing of all page and other views
• Defaults to using persistence, uses OS disk cache for hot data (has higher throughput then any of the above having persistence enabled)
• Supports both on-line as off-line processing

ZMQ

• The socket library that acts as a concurrency framework
• Faster than TCP, for clustered products and supercomputing
• Carries messages across inproc, IPC, TCP, and multicast
• Connect N-to-N via fanout, pubsub, pipeline, request-reply
• Asynch I/O for scalable multicore message-passing apps