Building Real-Time Analytics Systems: From Events to Insights with Apache Kafka and Apache Pinot
Gain deep insight into real-time analytics, including the features of these systems and the problems they solve. With this practical book, data engineers at organizations that use event-processing systems such as Kafka, Google Pub/Sub, and AWS Kinesis will learn how to analyze data streams in real time. The faster you derive insights, the quicker you can spot changes in your business and act accordingly.
Author Mark Needham from StarTree provides an overview of the real-time analytics space and an understanding of what goes into building real-time applications. The book's second part offers a series of hands-on tutorials that show you how to combine multiple software products to build real-time analytics applications for an imaginary pizza delivery service.
You will:
- Learn common architectures for real-time analytics
- Discover how event processing differs from real-time analytics
- Ingest event data from Apache Kafka into Apache Pinot
- Combine event streams with OLTP data using Debezium and Kafka Streams
- Write real-time queries against event data stored in Apache Pinot
- Build a real-time dashboard and order tracking app
- Learn how Uber, Stripe, and Just Eat use real-time analytics
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As a developer relations engineer, Mark helps users learn how to use Apache Pinot to build their real-time user-facing analytics applications. He also does developer experience, simplifying the getting started experience by making product tweaks and improvements to the documentation. Mark previously worked in Developer Relations, Product Engineering, and Field Engineering at Neo4j, where he co-authored O'Reilly's Graph Algorithms book.
