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  1. Stackups
  2. Application & Data
  3. Infrastructure as a Service
  4. Cluster Management
  5. Apache Mesos vs Zookeeper

Apache Mesos vs Zookeeper

OverviewComparisonAlternatives

Overview

Apache Mesos
Apache Mesos
Stacks306
Followers418
Votes31
GitHub Stars5.3K
Forks1.7K
Zookeeper
Zookeeper
Stacks889
Followers1.0K
Votes43

Apache Mesos vs Zookeeper: What are the differences?

Introduction

In this article, we will discuss the key differences between Apache Mesos and Zookeeper. Both Apache Mesos and Zookeeper are widely used distributed systems that provide different functionalities and features.

  1. Resource Management: Apache Mesos is primarily focused on resource management and sharing across different distributed frameworks, enabling efficient utilization of resources in a cluster. It provides a flexible and scalable framework for running applications. On the other hand, Zookeeper is a centralized service for maintaining configuration information, naming, synchronization, and providing group services. It is not specifically designed for resource management.

  2. Scheduling: Mesos includes a flexible and powerful scheduler that allows users to define their own scheduling policies. It provides fine-grained control over resource allocation and allows multiple frameworks to share resources in a cluster. Zookeeper, on the other hand, does not provide built-in scheduling capabilities but rather focus on coordination and synchronization among distributed applications.

  3. Design Philosophy: Apache Mesos follows a master-slave architecture, where the master node is responsible for resource allocation and scheduling decisions, while the slave nodes execute tasks. In contrast, Zookeeper follows a hierarchical structure with a single coordinator known as the "ensemble," which is responsible for maintaining consistency among distributed nodes.

  4. Fault Tolerance: Mesos is designed to be fault-tolerant by providing automatic failover and recovery mechanisms. It uses leader election and replication techniques to ensure high availability of the master node. Zookeeper also offers high availability and fault tolerance by using a quorum-based approach to replicate data across a cluster of nodes.

  5. Data Model: Mesos provides a flexible data model that allows users to define their own scheduling primitives and resource constraints. It supports fine-grained resource allocation and dynamic resource sharing. Zookeeper, on the other hand, follows a hierarchical data model similar to a file system, where data is organized in a tree-like structure called "Znodes."

  6. Use Cases: Apache Mesos is commonly used for large-scale distributed computing environments, such as data centers and cloud infrastructures. It provides a scalable and efficient platform for running diverse workloads. Zookeeper, on the other hand, is commonly used for coordinating and managing distributed systems, such as distributed databases, messaging systems, and web services.

In summary, Apache Mesos is a resource management platform that provides a scalable framework for running applications in a distributed environment, while Zookeeper is a centralized service for coordination and synchronization among distributed applications. Mesos focuses on resource management and scheduling, while Zookeeper focuses on maintaining consistency and providing group services.

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Detailed Comparison

Apache Mesos
Apache Mesos
Zookeeper
Zookeeper

Apache Mesos is a cluster manager that simplifies the complexity of running applications on a shared pool of servers.

A centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services. All of these kinds of services are used in some form or another by distributed applications.

Fault-tolerant replicated master using ZooKeeper;Scalability to 10,000s of nodes;Isolation between tasks with Linux Containers;Multi-resource scheduling (memory and CPU aware);Java, Python and C++ APIs for developing new parallel applications;Web UI for viewing cluster state
-
Statistics
GitHub Stars
5.3K
GitHub Stars
-
GitHub Forks
1.7K
GitHub Forks
-
Stacks
306
Stacks
889
Followers
418
Followers
1.0K
Votes
31
Votes
43
Pros & Cons
Pros
  • 21
    Easy scaling
  • 6
    Web UI
  • 2
    Fault-Tolerant
  • 1
    High-Available
  • 1
    Elastic Distributed System
Cons
  • 1
    Depends on Zookeeper
  • 1
    Not for long term
Pros
  • 11
    High performance ,easy to generate node specific config
  • 8
    Kafka support
  • 8
    Java
  • 5
    Spring Boot Support
  • 3
    Supports extensive distributed IPC
Integrations
Apache Aurora
Apache Aurora
No integrations available

What are some alternatives to Apache Mesos, Zookeeper?

Consul

Consul

Consul is a tool for service discovery and configuration. Consul is distributed, highly available, and extremely scalable.

Eureka

Eureka

Eureka is a REST (Representational State Transfer) based service that is primarily used in the AWS cloud for locating services for the purpose of load balancing and failover of middle-tier servers.

Nomad

Nomad

Nomad is a cluster manager, designed for both long lived services and short lived batch processing workloads. Developers use a declarative job specification to submit work, and Nomad ensures constraints are satisfied and resource utilization is optimized by efficient task packing. Nomad supports all major operating systems and virtualized, containerized, or standalone applications.

etcd

etcd

etcd is a distributed key value store that provides a reliable way to store data across a cluster of machines. It’s open-source and available on GitHub. etcd gracefully handles master elections during network partitions and will tolerate machine failure, including the master.

DC/OS

DC/OS

Unlike traditional operating systems, DC/OS spans multiple machines within a network, aggregating their resources to maximize utilization by distributed applications.

Mesosphere

Mesosphere

Mesosphere offers a layer of software that organizes your machines, VMs, and cloud instances and lets applications draw from a single pool of intelligently- and dynamically-allocated resources, increasing efficiency and reducing operational complexity.

Keepalived

Keepalived

The main goal of this project is to provide simple and robust facilities for loadbalancing and high-availability to Linux system and Linux based infrastructures.

Gardener

Gardener

Many Open Source tools exist which help in creating and updating single Kubernetes clusters. However, the more clusters you need the harder it becomes to operate, monitor, manage and keep all of them alive and up-to-date. And that is exactly what project Gardener focuses on.

SkyDNS

SkyDNS

SkyDNS is a distributed service for announcement and discovery of services. It leverages Raft for high-availability and consensus, and utilizes DNS queries to discover available services. This is done by leveraging SRV records in DNS, with special meaning given to subdomains, priorities and weights (more info here: http://blog.gopheracademy.com/skydns).

YARN Hadoop

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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