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Real-time Analytics with Storm and Cassandra

You're reading from  Real-time Analytics with Storm and Cassandra

Product type Book
Published in Mar 2015
Publisher
ISBN-13 9781784395490
Pages 220 pages
Edition 1st Edition
Languages
Author (1):
Shilpi Saxena Shilpi Saxena
Profile icon Shilpi Saxena
Toc

Table of Contents (19) Chapters close

Real-time Analytics with Storm and Cassandra
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Let's Understand Storm 2. Getting Started with Your First Topology 3. Understanding Storm Internals by Examples 4. Storm in a Clustered Mode 5. Storm High Availability and Failover 6. Adding NoSQL Persistence to Storm 7. Cassandra Partitioning, High Availability, and Consistency 8. Cassandra Management and Maintenance 9. Storm Management and Maintenance 10. Advance Concepts in Storm 11. Distributed Cache and CEP with Storm Quiz Answers Index

Columnar database fundamentals


One of the most important aspects of getting started with NoSQL data stores is getting to understand the fundamentals of columnar databases; or rather, let's use the actual term—column families.

This is a concept that has a variety of implementations in different NoSQL databases, for instance:

  • Cassandra: This is a key-value-pair-based NoSQL DB

  • Mongo DB: This is a document-based NoSQL DB

  • Neo4J: This is a graph DB

They differ from conventional RDBMS systems that are row-oriented in terms of the following:

  • Performance

  • Storage extendibility

  • Fault tolerance

  • Low or no licensing cost

But having iterated all the differences and benefits of NoSQL DBs, you must clearly understand that the shift to NoSQL is a shift of the entire paradigm of data storage, availability, and access—they are not a replacement for RDBMS.

In the RDBMS world, we are all used to creating tables, but here in Cassandra, we create column families where we define the metadata of the columns, but the columns...

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