Fast Data Architectures For Streaming Applications

E-Book

Fast Data Architectures For Streaming Applications

By Dean Wampler, Ph.D., Office of the CTO and Big Data Architect, Lightbend, Inc.

By Dean Wampler, Ph.D., Office of the CTO and Big Data Architect, Lightbend, Inc. and Author Two

Why have stream-oriented data systems become so popular, when batch-oriented systems have served big data needs for many years? In this report, author Dean Wampler examines the rise of streaming systems for handling time-sensitive problems—like detecting fraudulent financial activity as it happens. You’ll explore the characteristics of fast data architectures, along with several open source tools for implementing them.

Batch-mode processing isn’t going away, but exclusive use of these systems is now a competitive disadvantage. You’ll learn that, while fast data architectures are much harder to build, they represent the state of the art for dealing with mountains of data that require immediate attention.

  • Learn step-by-step how a basic fast data architecture works
  • Understand why event logs are the core abstraction for streaming architectures, while message queues are the core integration tool
  • Use methods for analyzing infinite data sets, where you don’t have all the data and never will
  • Take a tour of open source streaming engines, and discover which ones work best for different use cases
  • Get recommendations for making real-world streaming system responsive, resilient, elastic, and message driven
  • Explore an example streaming application for the IoT: telemetry ingestion and anomaly detection for home automation systems

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About Author

Dean Wampler, Ph.D., Office of the CTO and Big Data Architect, Lightbend, Inc.

Dean Wampler, Ph.D., is a member of the Office of the CTO and the Architect for Big Data Products and Services at Lightbend. He uses Scala and Functional Programming to build Big Data systems using Spark, Mesos, Hadoop, the Lightbend Reactive Platform, and other tools. Dean is the author or co-author of three O'Reilly books on Scala, Functional Programming, and Hive. He contributes to several open source projects (including Spark) and he co-organizes and speaks at many technology conferences and Chicago-based user groups. He has B.S. and M.S. degrees in Physics from the University of Virginia and a Ph.D. in Theoretical Physics from the University of Washington.

About Authors

Dean Wampler, Ph.D., Office of the CTO and Big Data Architect, Lightbend, Inc.

Dean Wampler, Ph.D., is a member of the Office of the CTO and the Architect for Big Data Products and Services at Lightbend. He uses Scala and Functional Programming to build Big Data systems using Spark, Mesos, Hadoop, the Lightbend Reactive Platform, and other tools. Dean is the author or co-author of three O'Reilly books on Scala, Functional Programming, and Hive. He contributes to several open source projects (including Spark) and he co-organizes and speaks at many technology conferences and Chicago-based user groups. He has B.S. and M.S. degrees in Physics from the University of Virginia and a Ph.D. in Theoretical Physics from the University of Washington.

Author Two

Author Two Bio

About Lightbend

Lightbend (Twitter: @Lightbend) provides the leading Reactive application development platform for building distributed systems. Based on a message-driven runtime, these distributed systems, which include microservices and streaming fast data applications, can effortlessly scale on multi-core and cloud architectures. Many of the most admired brands around the globe are transforming their businesses with our platform, engaging billions of users every day through software that is changing the world. For more information on Lightbend, visit: lightbend.com