analytics large database real time
Recently, I was reading Todd Hoff's write-up on FaceBook real time analytics system . As usual, Todd did an excellent job in summarizing this video from Engineering Manager at Facebook Alex Himel. In the first post, I’d like to summarize the case study, and consider some things that
scalibity
Mozilla processes TB's of Firefox crash reports daily using HBase, Hadoop, Python and Thrift protocol. The project is called Socorro, a system for collecting, processing, and displaying crash reports from clients. Today the Socorro application stores about 2.6 million crash reports per day. During peak traffic, it
Database
In this post i wanted to spend sometime on the CAP theorem and clarify some of the confusion that i often see when people associate CAP with scalability without fully understanding the implications that comes with it and the alternative approaches You can read the full article here
databases
Terrastore is a new-born document store which provides advanced scalability and elasticity features without sacrificing consistency. Here are a few highlights: * Ubiquitous: based on the universally supported HTTP protocol. * Distributed: nodes can run and live everywhere on your network. * Elastic: you can add and remove nodes dynamically to/from your
Scalability
The High Scalable Systems (i.e. Websites) such as: Google, Facebook, Amazon, etc. need high scalable storage system that can deal with huge amount of data with high availability and reliability. Building large systems on top of a traditional RDBMS data storage layer is no longer good enough. This presentation
Scalability
Distributed systems are not typically a place domain driven design is applied. Distributed processing projects often start with an overall architecture vision and the idea about a processing model which basically drives the whole thing, including object design if it exists at all. Elaborate object designs are thought of as
Memcached
A software-based distributed caching system such as memcached is an important piece of today's largest Internet sites that support millions of concurrent users and deliver user-friendly response times. The distributed nature of memcached design transforms 1000s of servers into one large caching pool with gigabytes of memory per
Example
Making the world's knowledge computable Today's Wolfram|Alpha is the first step in an ambitious, long-term project to make all systematic knowledge immediately computable by anyone. You enter your question or calculation, and Wolfram|Alpha uses its built-in algorithms and growing collection of data to compute
Scalability
An interesting post on DataCenterKnowledge! * 1&1 Internet: 55,000 servers * Rackspace: 50,038 servers * The Planet: 48,500 servers * Akamai Technologies: 48,000 servers * OVH: 40,000 servers * SBC Communications: 29,193 servers * Verizon: 25,788 servers * Time Warner Cable: 24,817 servers * SoftLayer: 21,000 servers * AT&
Scalability
GemFire Enterprise is in-memory distributed data management platform that pools memory (and CPU, network and optionally local disk) across multiple processes to manage application objects and behavior. With the 6.0 release, GemFire has reached a stage of maturity in its evolution. GemStone touts this version as the true '
Memcached
Memcached is generally treated as a black box. But what if you really need to know what's in there? Not for runtime purposes, but for optimization and capacity planning? Read more on Evan Weaver, a software developer working for Twitter (a contributor for Rails core and Mongrel).
Scalability
I found this resources: High Scalable Architecture: - YouTube Architecture - Facebook Chat Architecture - Amazon Architecture Blogs: - Scalability Guidelines for building scalable software system (part 1) - Scalability Guidelines for building scalable software system (part 2) - Scalability Guidelines for building scalable software system (part 3) - Scalability