In an enterprise, data is generated from all the software that is participating in day-to-day operations. This data has different formats, and bringing in this data for big-data processing requires a storage system that is flexible enough to accommodate a data with varying data models. A NoSQL database, by its design, is best suited for this kind of storage requirements. One of the primary objectives of NoSQL is horizontal scaling, that is, the P in CAP theorem, but this works at the cost of sacrificing Consistency or Availability. Visit http://en.wikipedia.org/wiki/CAP_theorem to understand more about CAP theorem.
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You're reading from Scaling Big Data with Hadoop and Solr, Second Edition
Hrishikesh Vijay Karambelkar is an innovator and an enterprise architect with 16 years of software design and development experience, specifically in the areas of big data, enterprise search, data analytics, text mining, and databases. He is passionate about architecting new software implementations for the next generation of software solutions for various industries, including oil and gas, chemicals, manufacturing, utilities, healthcare, and government infrastructure. In the past, he has authored three books for Packt Publishing: two editions of Scaling Big Data with Hadoop and Solr and one of Scaling Apache Solr. He has also worked with graph databases, and some of his work has been published at international conferences such as VLDB and ICDE.
Read more about Hrishikesh Vijay Karambelkar
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Hrishikesh Vijay Karambelkar is an innovator and an enterprise architect with 16 years of software design and development experience, specifically in the areas of big data, enterprise search, data analytics, text mining, and databases. He is passionate about architecting new software implementations for the next generation of software solutions for various industries, including oil and gas, chemicals, manufacturing, utilities, healthcare, and government infrastructure. In the past, he has authored three books for Packt Publishing: two editions of Scaling Big Data with Hadoop and Solr and one of Scaling Apache Solr. He has also worked with graph databases, and some of his work has been published at international conferences such as VLDB and ICDE.
Read more about Hrishikesh Vijay Karambelkar