Facebook's New Realtime Analytics System: HBase to Process 20 Billion Events Per Day - High Scalability -
Facebook did it again. They've built another system capable of doing something useful with ginormous streams of realtime data. Last time we saw Facebook release their New Real-Time Messaging System: HBase To Store 135+ Billion Messages A Month. This time it's a realtime analytics system handling over 20 billion events per day (200,000 events per second) with a lag of less than 30 seconds. Alex Him
Facebook's New Real-time Messaging System: HBase to Store 135+ Billion Messages a Month - High Scalability -
You may have read somewhere that Facebook has introduced a new Social Inbox integrating email, IM, SMS, text messages, on-site Facebook messages. All-in-all they need to store over 135 billion messages a month. Where do they store all that stuff? Facebook's Kannan Muthukkaruppan gives the surprise answer in The Underlying Technology of Messages: HBase. HBase beat out MySQL, Cassandra, and a few o
6 Scalability Lessons - High Scalability -
Jesper Söderlund not only put together a few interesting scalability patterns, he also came up with a few interesting scalability lessons: Lesson #1. Put Smarty compile and template caches on an active-active DRBD cluster with high load and your servers will DIE!Lesson #2. Don't use out-of-the-box configurations.Lesson #3. Single points of contention will eventually become a bottleneck.Lesson #4.
Pairing NoSQL and Relational Data Storage: MySQL with MongoDB - High Scalability -
I’ve largely steered clear of publicly commenting on the “NoSQL vs. Relational” conflict. Keeping in mind that this argument is more about currently available solutions and the features their developers have chosen to build in, I’d like to dig into this and provide a decidedly neutral viewpoint. In fact, by erring on the side of caution, I’ve inadvertently given myself plenty of time to consider t
7 Scaling Strategies Facebook Used to Grow to 500 Million Users - High Scalability -
Robert Johnson, a director of engineering at Facebook, celebrated Facebook's monumental achievement of reaching 500 million users by sharing the scaling principles that helped reach that milestone. In case you weren't suitably impressed by the 500 million user number, Robert ratchets up the numbers game with these impressive figures: 1 million users per engineer 500 million active users 100 billio
Scaling Twitter: Making Twitter 10000 Percent Faster - High Scalability -
Update 6: Some interesting changes from Twitter's Evan Weaver: everything in RAM now, database is a backup; peaks at 300 tweets/second; every tweet followed by average 126 people; vector cache of tweet IDs; row cache; fragment cache; page cache; keep separate caches; GC makes Ruby optimization resistant so went with Scala; Thrift and HTTP are used internally; 100s internal requests for every exter
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