Big Data, Principles and Best Practices of Scalable Realtime Data Systems (1 ed)

Web-scale applications—such as social networks, real-time analytics platforms, and e-commerce sites—handle massive volumes of data that exceed the capabilities of traditional database systems. These applications demand architectures built on clusters of machines, capable of storing and processing data at any size or speed. Importantly, scalability does not have to come at the cost of simplicity.

Big Data provides a practical guide to building large-scale data systems using an architecture designed to capture and analyze web-scale data. The book introduces the Lambda Architecture, a scalable and easy-to-understand approach that even a small team can implement and maintain. You’ll explore the theory behind big data systems and learn how to put it into practice, while gaining hands-on experience with essential technologies like Hadoop, Storm, and NoSQL databases.

No prior experience with large-scale data analysis or NoSQL tools is required, though familiarity with traditional databases will be helpful.

Inside this book, you’ll discover:

• A comprehensive introduction to big data systems
• Real-time processing of web-scale data
• Key tools such as Hadoop, Cassandra, and Storm
• How to extend traditional database skills for big data applications