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are so different one might expect two different systems to be used, but apparently HBase works well enough for both. How they handle generic search functionality isn't clear as that's not a strength of HBase, though it does integrate with various search systems.
Makes sense. You read what's current in your inbox once and then rarely if ever take a look at it again. These Adidas Los Angeles Sizing
What they needed was a system that could handle two types of data patterns:
chose HBase because they monitored their usage and figured out what the really needed. Adidas Originals Trainers Foot Locker
Has a simpler consistency model than Cassandra.
Very good scalability and performance for their data patterns.
Most feature rich for their requirements: auto load balancing and failover, compression support, multiple shards per server, etc.
HBase is a scaleout table store supporting very high rates of row level updates over massive amounts of data. Exactly what is needed for a Messaging system. HBase is also a column based key value store built on the BigTable model. It's good at fetching rows by key or scanning ranges of rows and filtering. Also what is needed Adidas Los Angeles Eastbay
An ever growing set of data that rarely gets accessed
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for a Messaging system. Complex queries are not supported however. Queries are generally given over to an analytics tool like Hive, which created to make sense of their multi petabyte data warehouse, and Hive is based on Hadoop's file system, HDFS, which is also used by HBase.
The Updated Big List Of Articles On The Amazon OutageYou may have read somewhere that has introduced a new Social Inbox integrating email, IM, SMS, text messages, on site messages. All in all they need to store over 135 billion messages a month. Where do they store all that stuff? 's Kannan Muthukkaruppan gives the surprise answer in The Underlying Technology of Messages: HBase. HBase beat out MySQL, Cassandra, and a few others.
Some key aspects of their system:
Billion Messages a Month
A short set of temporal data that tends to be volatile
Why a surprise? created Cassandra and it was purpose built for an inbox type application, but they found Cassandra's eventual consistency model wasn't a good match for their new real time Messages product. also has an extensive MySQL infrastructure, but they found performance suffered as data set and indexes grew larger. And they could have built their own, but they chose HBase.
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