This book delves into the core principles and practices that drive real-time data processing, covering essential topics such as latency, throughput, and data consistency. With a focus on practical applications, readers will explore a range of technologies and tools including Apache Kafka, Apache Flink, Redis, and more, providing a solid foundation for building scalable and reliable real-time systems.
Key highlights of the book include:
With clear explanations, practical examples, and a focus on actionable insights, Real-time Data Processing is an essential resource for anyone looking to harness the power of data in real-time.
Key highlights of the book include:
- Fundamental Concepts: Understand the basics of real-time data processing and how it differs from traditional batch processing.
- Technologies and Tools: Get to know the leading frameworks, databases, and data integration tools that power real-time processing.
- Design Considerations: Learn how to optimize for latency, scalability, and fault tolerance in real-time systems.
- Real-world Case Studies: Discover how real-time data processing is applied in various industries, including finance, healthcare, e-commerce, and smart cities.
- Future Trends: Stay ahead of the curve with insights into emerging technologies such as edge computing, AI integration, and 5G.
With clear explanations, practical examples, and a focus on actionable insights, Real-time Data Processing is an essential resource for anyone looking to harness the power of data in real-time.
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