What is a primary characteristic of Lambda architecture?

What is a primary characteristic of Lambda architecture?

• A. It emphasizes only a singular path for data processing
• B. It utilizes a batch path focused on consistency and availability
• C. It requires that speed path is less prioritized than batch path
• D. It ignores partition tolerance as a key operational feature

Answer: (B)

Lambda architecture is designed to handle large volumes of data by providing a robust framework that combines both batch processing and real-time stream processing. One of its primary characteristics is the batch path, which is responsible for processing large datasets with a focus on consistency and availability. This approach allows for thorough data analysis and ensures that the data remains reliable over time. In Lambda architecture, the batch path can yield accurate and comprehensive results, which may not be possible with real-time processing alone. This dual approach is essential for systems that require both immediate insights and durable, consistent processing outcomes, highlighting the architecture’s capability to effectively balance speed and reliability. The other options either misrepresent the key features of Lambda architecture or do not accurately capture its primary focus. For instance, the emphasis of Lambda architecture is not solely on a singular path for data processing, and it certainly does not prioritize speed less than the batch path, as both paths play crucial roles. Additionally, partition tolerance is a vital aspect of distributed systems, and it is not ignored in the context of Lambda architecture, which is designed to maintain operation despite network partitions.

Lambda architecture is designed to handle large volumes of data by providing a robust framework that combines both batch processing and real-time stream processing. One of its primary characteristics is the batch path, which is responsible for processing large datasets with a focus on consistency and availability. This approach allows for thorough data analysis and ensures that the data remains reliable over time.

In Lambda architecture, the batch path can yield accurate and comprehensive results, which may not be possible with real-time processing alone. This dual approach is essential for systems that require both immediate insights and durable, consistent processing outcomes, highlighting the architecture’s capability to effectively balance speed and reliability.

The other options either misrepresent the key features of Lambda architecture or do not accurately capture its primary focus. For instance, the emphasis of Lambda architecture is not solely on a singular path for data processing, and it certainly does not prioritize speed less than the batch path, as both paths play crucial roles. Additionally, partition tolerance is a vital aspect of distributed systems, and it is not ignored in the context of Lambda architecture, which is designed to maintain operation despite network partitions.