What is Lambda Architecture and its use cases?
An example of an AI chatbot conversation about Lambda Architecture and its practical applications.
What is Lambda Architecture and why is it important?
Lambda Architecture is a data-processing architecture designed to handle massive quantities of data by using both batch and stream processing. It's important because it provides a framework for building robust, fault-tolerant systems that can process real-time data.
Can you give me some real-world use cases of Lambda Architecture?
Sure! Some real-world use cases include real-time analytics for social media platforms, fraud detection in financial services, and recommendation systems for e-commerce.
What are the main components of Lambda Architecture?
The main components are the Batch Layer, Speed Layer, and Serving Layer. The Batch Layer manages the master dataset, the Speed Layer processes real-time data, and the Serving Layer merges the results for querying.
What are the advantages and disadvantages of using Lambda Architecture?
Advantages include scalability and fault tolerance, while disadvantages can be complexity in implementation and maintenance.
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