Book Image

Seven NoSQL Databases in a Week

By : Sudarshan Kadambi, Xun (Brian) Wu
Book Image

Seven NoSQL Databases in a Week

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 (16 chapters)
Title Page
Copyright and Credits
Dedication
Packt Upsell
Contributors
Preface
Index

Advanced topics


For readers who feel they have a good grasp of HBase fundamentals at this point, we will now cover advanced topics such as high availability, coprocessors, and SQL over HBase.

HBase high availability

In any enterprise looking to build mission-critical applications on top of HBase, the main questions on everybody's minds are Is the database reliable? What if it goes down? Under what conditions does it fail? How long will it take for the system to be functional again? Will there be lingering effects?

Let's try and understand each piece of this puzzle. As we've discussed, HBase favors strong consistency, and consequently makes a single RegionServer responsible for all reads and writes for a given key. When that RegionServer goes down, we lose access to the data stored within it and are unable to perform reads and writes with that data. However, since the underlying data is stored on HDFS, the loss of access is only temporary. Once the regions are reassigned to a different RegionServer...