In this special technology white paper, The Lambda Architecture Simplified, you’ll learn about how the Lambda Architecture aims to satisfy the needs for a robust system that is fault-tolerant, both against hardware failures and human mistakes, being able to serve a wide range of workloads and use cases, and in which low-latency reads and updates are required.
In his book, Big Data: Principles and Best Practices of Scalable Real-time Data Systems, Nathan Marz coined the term Lambda Architecture to describe a generic, scalable and fault-tolerant data processing architecture based on his experience in working on distributed systems at Backtype and Twitter.
The paper explores what The Lambda Architecture is and what it isn’t. What it is, is a sensible set of data engineering practices, which you should be applying anyway, plus a clever (but transitional) double-write approach to add a low-latency fast track to existing big data systems. Throughout the white paper, you’ll find details of the technologies and data processing requirements that will help you implement a simplified Lambda Architecture. The white paper includes the following high level topics:
- A Brief History of the Lambda Architecture
- Rethinking the Lambda Architecture
- Lambda in Production
The pace of data is not slowing. Applications of today are built with infinite data sets in mind. As these real-time applications become the norm, and batch processing becomes a relic of the past, digital enterprises will implement memory-optimized, distributed data systems to simplify Lambda Architectures for real-time data processing and exploration.
The Lambda Architecture Simplified white paper is available for download in PDF from the insideBIGDATA White Paper Library, courtesy of MemSQL.
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