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Peloton vs YARN Hadoop: What are the differences?

# Introduction
When it comes to distributed computing frameworks, Peloton and YARN Hadoop are two popular choices. While both serve the purpose of resource management, they have distinct differences that make them suitable for different use cases. Below, we will explore the key differences between Peloton and YARN Hadoop.

1. **Architecture**: Peloton follows a microservices architecture where each component is built as an independent service, providing flexibility and scalability. In contrast, YARN Hadoop is based on a monolithic architecture, where all components are tightly coupled, which can limit scalability.

2. **Scheduling Algorithm**: Peloton utilizes an advanced scheduling algorithm based on resource requirements, job dependencies, and constraints to optimize resource allocation efficiently. On the other hand, YARN Hadoop uses a traditional scheduler that might not be as flexible in handling complex job scenarios.

3. **Containerization**: Peloton leverages container technology, like Docker and Kubernetes, to isolate and manage workloads effectively. In comparison, YARN Hadoop uses its own containerization framework, which may not be as widely adopted or supported.

4. **Real-time Processing**: Peloton is designed to support real-time processing, enabling low-latency workflows and streaming applications. In contrast, YARN Hadoop is more suitable for batch processing and might not perform as efficiently for real-time use cases.

5. **Job Isolation**: Peloton provides better job isolation by segregating workloads in separate containers, preventing interference and resource contention between different tasks. YARN Hadoop, while offering isolation to some extent, might face challenges in fully isolating jobs running on the same node.

6. **Ecosystem Integration**: YARN Hadoop has a strong integration with the Hadoop ecosystem, making it a suitable choice for organizations already using Hadoop for big data processing. Peloton, being a newer framework, might not have the same level of ecosystem integration with existing technologies.

In Summary, Peloton and YARN Hadoop differ in architecture, scheduling algorithm, containerization approach, support for real-time processing, job isolation capabilities, and ecosystem integration, catering to distinct requirements in the world of distributed computing.
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    What is Peloton?

    A Unified Resource Scheduler to co-schedule mixed types of workloads such as batch, stateless and stateful jobs in a single cluster for better resource utilization. Designed for web-scale companies with millions of containers and tens of thousands of nodes.

    What is YARN Hadoop?

    Its fundamental idea is to split up the functionalities of resource management and job scheduling/monitoring into separate daemons. The idea is to have a global ResourceManager (RM) and per-application ApplicationMaster (AM).

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    Mar 24 2021 at 12:57PM

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