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Seven NoSQL Databases in a Week

Seven NoSQL Databases in a Week

By : Sudarshan Kadambi, Xun (Brian) Wu
3.5 (6)
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Seven NoSQL Databases in a Week

Seven NoSQL Databases in a Week

3.5 (6)
By: Sudarshan Kadambi, Xun (Brian) Wu

Overview of this book

This is the golden age of open source NoSQL databases. With enterprises having to work with large amounts of unstructured data and moving away from expensive monolithic architecture, the adoption of NoSQL databases is rapidly increasing. Being familiar with the popular NoSQL databases and knowing how to use them is a must for budding DBAs and developers. This book introduces you to the different types of NoSQL databases and gets you started with seven of the most popular NoSQL databases used by enterprises today. We start off with a brief overview of what NoSQL databases are, followed by an explanation of why and when to use them. The book then covers the seven most popular databases in each of these categories: MongoDB, Amazon DynamoDB, Redis, HBase, Cassandra, In?uxDB, and Neo4j. The book doesn't go into too much detail about each database but teaches you enough to get started with them. By the end of this book, you will have a thorough understanding of the different NoSQL databases and their functionalities, empowering you to select and use the right database according to your needs.
Table of Contents (10 chapters)
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HBase

Systems aren't designed in a vacuum. Each system reflects a long line of prior work. HBase is no exception. So where did HBase's developers draw their inspiration from?

In 2006, engineers at Google published a paper on a system they called Bigtable. It described the data model, semantics, and inner workings of a distributed database, which itself drew inspiration from a line of prior work, such as Chord, Tapestry, and C-Store.

Bigtable followed Google File System (GFS), the inspiration behind HDFS at Google, and was meant to offer record-level random read/write capabilities that were missing in GFS. Bigtable was initially used to serve workloads such as Google Analytics (for storing site metrics), and continues to be a popular storage choice at Google, despite newer systems, such as Spanner, that have been developed since then.

In 2007, engineers at a search...

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