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Learning Apache Cassandra

You're reading from   Learning Apache Cassandra Managing fault-tolerant, scalable data with high performance

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Product type Paperback
Published in Apr 2017
Publisher
ISBN-13 9781787127296
Length 360 pages
Edition 2nd Edition
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Author (1):
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Sandeep Yarabarla Sandeep Yarabarla
Author Profile Icon Sandeep Yarabarla
Sandeep Yarabarla
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Table of Contents (15) Chapters Close

Preface 1. Getting Up and Running with Cassandra FREE CHAPTER 2. The First Table 3. Organizing Related Data 4. Beyond Key-Value Lookup 5. Establishing Relationships 6. Denormalizing Data for Maximum Performance 7. Expanding Your Data Model 8. Collections, Tuples, and User-Defined Types 9. Aggregating Time-Series Data 10. How Cassandra Distributes Data 11. Cassandra Multi-Node Cluster 12. Application Development Using the Java Driver 13. Peeking under the Hood 14. Authentication and Authorization

Challenges of modern applications

Before we delve into the shortcomings of relational systems to handle big data, let's take a look at some of the challenges faced by modern web-facing and big data applications.

Later, this will give an insight into how NoSQL data stores or Cassandra, in particular, help solve these issues:

  • One of the most important challenges faced by a web-facing application is the ability to handle a large number of concurrent users. Think of a search engine such as Google, which handles millions of concurrent users at any given point of time, or a large online retailer. The response from these applications should be swift even as the number of users keeps on growing.
  • Modern applications need to be able to handle large amounts of data, which can scale to several petabytes of data and beyond. Consider a large social network with a few hundred million users:
    • Think of the amount of data generated in tracking and managing those users
    • Think of how this data can be used for analytics
  • Business-critical applications should continue running without much impact even when there is a system failure or multiple system failures (server failure, network failure, and so on). The applications should be able to handle failures gracefully without any data loss or interruptions.
  • These applications should be able to scale across multiple data centers and geographical regions to support customers from different regions around the world with minimum delay. Modern applications should be implementing fully distributed architectures and should be capable of scaling out horizontally to support any data size or any number of concurrent users.
You have been reading a chapter from
Learning Apache Cassandra - Second Edition
Published in: Apr 2017
Publisher:
ISBN-13: 9781787127296
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