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Over the last couple years, we see an emerging data storage mechanism for storing large scale of data. These storage solution differs quite significantly with the RDBMS model and is also known as the NOSQL. Some of the key players include ... GoogleBigTable, HBase, Hypertable AmazonDynamo , Voldemort, Cassendra, Riak Redis CouchDB , MongoDB These solutions has a number of characteristics in common Key value store Run on large number of commodity machines Data are partitioned and replicated among these machines Relax the data consistency requirement.
In my previous post, I talk about the methodology of transforming a sequential algorithm into parallel. After that, we can implement the parallel algorithm, one of the popular framework we can use is the Apache Opensource Hadoop Map/Reduce framework. Functional Programming
With BigData comes BigStorage costs. One way to store less is simply not to store the same data twice . That's the radically simple and powerful notion behind data deduplication . If you are one of those who got a good laugh out of the idea of eliminating SQL queries as a rather obvious scalability strategy, you'll love this one, but it is a powerful feature and one I don't hear talked about outside the enterprise.
In a series of blogs, Monitis has begun providing guidance on picking the right NoSQL database storage tool that meets your company’s needs. In our previous blog, we offered a comprehensive overview of why NoSQL technology is important and how it compares with Relational Database Management Systems (RDBMSs). Now, we’d like to get a bit more specific and review various brands. We hope that this information will help choosing NoSQL DBs such as Apache Cassandra, MongoDB, CouchDB, Redis, Riak, HBase and others…easier. After all, you want to make sure that your data is being stored safely. Aren’t there enough worries out there about data security – whether the data is being stored on the cloud or behind your internal, private firewall?