Lambda Architecture, is designed to handle massive quantities of data by using both batch and real-time processing methods.
It consists of three layers:
- Batch layer, which processes large volumes of data in bulk and stores it in a master dataset
- Speed layer, which handles real-time data processing to provide low-latency updates
- Serving layer, which merges results from both the batch and speed layers to deliver a comprehensive view of the data.
This architecture ensures fault tolerance, scalability, and low-latency access to data. By combining historical batch data with real-time streaming data, Lambda Architecture allows for robust and flexible data analytics, making it suitable for applications requiring accurate, timely insights, such as recommendation systems, social media analytics, and financial analysis.