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Hadoop VS Ansible

Compare Hadoop VS Ansible and see what are their differences

Unimus
Unimus is a Network Automation and Configuration management (NCM) solution designed for fast deployment network-wide and ease of use. Unimus does not require learning any abstraction or templating languages, and does not require any coding skills. featured
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Hadoop logo Hadoop

Open-source software for reliable, scalable, distributed computing

Ansible logo Ansible

Radically simple configuration-management, application deployment, task-execution, and multi-node orchestration engine
  • Hadoop Landing page
    Landing page //
    2021-09-17
  • Ansible Landing page
    Landing page //
    2023-02-05

Hadoop features and specs

  • Scalability
    Hadoop can easily scale from a single server to thousands of machines, each offering local computation and storage.
  • Cost-Effective
    It utilizes a distributed infrastructure, allowing you to use low-cost commodity hardware to store and process large datasets.
  • Fault Tolerance
    Hadoop automatically maintains multiple copies of all data and can automatically recover data on failure of nodes, ensuring high availability.
  • Flexibility
    It can process a wide variety of structured and unstructured data, including logs, images, audio, video, and more.
  • Parallel Processing
    Hadoop's MapReduce framework enables the parallel processing of large datasets across a distributed cluster.
  • Community Support
    As an Apache project, Hadoop has robust community support and a vast ecosystem of related tools and extensions.

Possible disadvantages of Hadoop

  • Complexity
    Setting up, maintaining, and tuning a Hadoop cluster can be complex and often requires specialized knowledge.
  • Overhead
    The MapReduce model can introduce additional overhead, particularly for tasks that require low-latency processing.
  • Security
    While improvements have been made, Hadoop's security model is considered less mature compared to some other data processing systems.
  • Hardware Requirements
    Though it can run on commodity hardware, Hadoop can still require significant computational and storage resources for larger datasets.
  • Lack of Real-Time Processing
    Hadoop is mainly designed for batch processing and is not well-suited for real-time data analytics, which can be a limitation for certain applications.
  • Data Integrity
    Distributed systems face challenges in maintaining data integrity and consistency, and Hadoop is no exception.

Ansible features and specs

  • Agentless
    Ansible is agentless, meaning it doesn't require any software to be installed on the remote nodes. This simplifies management and reduces overhead.
  • Ease of Use
    Ansible uses a simple, easy-to-read YAML syntax for its playbooks, reducing the learning curve and making it accessible to those without extensive programming experience.
  • Scalability
    Ansible is designed to handle large-scale deployments, making it suitable for managing numerous machines or services efficiently.
  • Extensive Modules
    Ansible has a rich library of modules that support a wide variety of system tasks, cloud providers, and application deployments, offering great versatility.
  • Strong Community
    There is a large and active Ansible community that contributes to its development and provides support, which can be valuable for troubleshooting and learning best practices.
  • Idempotency
    Tasks in Ansible are idempotent, meaning they can be run multiple times without changing the system beyond the intended final state, ensuring reliable deployments.

Possible disadvantages of Ansible

  • Performance Overhead
    Being agentless, Ansible relies on SSH for communication with nodes, which can add performance overhead, especially when managing a large number of hosts.
  • Limited Windows Support
    Ansible's core is primarily designed for Unix-like systems, and while there is support for Windows, it's not as robust or as seamless as it is for Unix/Linux systems.
  • Lack of Built-in Error Handling
    Ansible's error handling is somewhat rudimentary out-of-the-box. Complex error handling scenarios often require custom solutions, which can complicate playbooks.
  • Learning Curve for Complex Scenarios
    While simple tasks are easy to set up, more complex configurations can become challenging quickly and may require a deep understanding of Ansible's modules and templating.
  • Reliance on YAML
    The use of YAML, while human-readable, can be prone to syntax errors such as incorrect indentation, which can potentially lead to hard-to-track-down bugs.
  • Dependency on Python
    Ansible requires Python to be installed on managed nodes. This could be an issue in environments where it's not feasible or desired to have Python installed.

Hadoop videos

+ Add

What is Big Data and Hadoop?

More videos:

  • Review - Product Ratings on Customer Reviews Using HADOOP.
  • Tutorial - Hadoop Tutorial For Beginners | Hadoop Ecosystem Explained in 20 min! - Frank Kane

Ansible videos

+ Add

What Is Ansible? | How Ansible Works? | Ansible Tutorial For Beginners | DevOps Tools | Simplilearn

More videos:

  • Review - Automation with Ansible Playbooks | Review on Ansible Architecture
  • Review - Book Review : Mastering Ansible (Jesse Keating) by Zareef Ahmed

Category Popularity

0-100% (relative to Hadoop and Ansible)

Hadoop

Ansible

Databases
100 100%
Databases
0% 0
DevOps Tools
0 0%
DevOps Tools
100% 100
Big Data
100 100%
Big Data
0% 0
Continuous Integration
0 0%
Continuous Integration
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Hadoop and Ansible

Hadoop Reviews

A List of The 16 Best ETL Tools And Why To Choose Them
Companies considering Hadoop should be aware of its costs. A significant portion of the cost of implementing Hadoop comes from the computing power required for processing and the expertise needed to maintain Hadoop ETL, rather than the tools or storage themselves.
Source: www.datacamp.com
16 Top Big Data Analytics Tools You Should Know About
Hadoop is an Apache open-source framework. Written in Java, Hadoop is an ecosystem of components that are primarily used to store, process, and analyze big data. The USP of Hadoop is it enables multiple types of analytic workloads to run on the same data, at the same time, and on a massive scale on industry-standard hardware.
Source: www.analytixlabs.co.in
5 Best-Performing Tools that Build Real-Time Data Pipeline
Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than relying on hardware to deliver high-availability, the library itself is...
Source: www.analyticsinsight.net

Ansible Reviews

What Are The Best Alternatives To Ansible? | Attune, Jenkins &, etc.
To put it simply, Ansible automates a wide range of IT aspects that includes configuration management, application deployment, cloud provisioning, etc. Plus, while using Ansible, you can patch your application, automate deployments, and run compliances and governance on your application. You can easily manage it by using a web interface known as Ansible Tower. Furthermore,...
Source: www.apzomedia.com
Best 8 Ansible Alternatives & equivalent in 2022
Ansible is a simple IT automation tool that is easy to deploy. It connects to your nodes and pushes out small programs called “Ansible modules” to those nodes. Then it executes these models over SSH and removes them when finished. The library of modules will reside on any machine, therefore there is no requirement for any servers and databases.
Source: www.guru99.com
Top 5 Ansible Alternatives in 2022: Server Automation Solutions by Alexander Fashakin on the 19th Aug 2021 facebook Linked In Twitter
Your project connects to Ansible through nodes called Ansible Modules. You can use these modules to manage your project. As an agentless architecture, Ansible allows you to run modules on any system or server. It doesn’t require client/server software or an agent to be installed. With Ansible, you can use Python Paramiko modules or SSH protocols.
Source: www.servertribe.com
Ansible vs Chef: What’s the Difference?
For Ansible, Simplilearn presents the Ansible Foundation Training Course. Ansible 2.0, a simple, popular, agent-free tool in the automation domain, helps increase team productivity and improve business outcomes. Learn with
Source: www.simplilearn.com
Chef vs Puppet vs Ansible
Ansible supports considerable ease of learning for the management of configurations due to YAML as the foundation language. YAML (Yet Another Markup Language) is closely similar to English and is human-readable. The server can help in pushing configurations to all the nodes. The applications of Ansible are clearly suitable for real-time execution along with the facility of...
Source: www.whizlabs.com

Social recommendations and mentions

Based on our record, Hadoop should be more popular than Ansible. It has been mentiond 25 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Hadoop mentions (25)

  • Apache Hadoop: Open Source Business Model, Funding, and Community
    This post provides an in‐depth look at Apache Hadoop, a transformative distributed computing framework built on an open source business model. We explore its history, innovative open funding strategies, the influence of the Apache License 2.0, and the vibrant community that drives its continuous evolution. Additionally, we examine practical use cases, upcoming challenges in scaling big data processing, and future... - Source: dev.to / 13 days ago
  • What is Apache Kafka? The Open Source Business Model, Funding, and Community
    Modular Integration: Thanks to its modular approach, Kafka integrates seamlessly with other systems including container orchestration platforms like Kubernetes and third-party tools such as Apache Hadoop. - Source: dev.to / 13 days ago
  • India Open Source Development: Harnessing Collaborative Innovation for Global Impact
    Over the years, Indian developers have played increasingly vital roles in many international projects. From contributions to frameworks such as Kubernetes and Apache Hadoop to the emergence of homegrown platforms like OpenStack India, India has steadily carved out a global reputation as a powerhouse of open source talent. - Source: dev.to / 19 days ago
  • Unveiling the Apache License 2.0: A Deep Dive into Open Source Freedom
    One of the key attributes of Apache License 2.0 is its flexible nature. Permitting use in both proprietary and open source environments, it has become the go-to choice for innovative projects ranging from the Apache HTTP Server to large-scale initiatives like Apache Spark and Hadoop. This flexibility is not solely legal; it is also philosophical. The license is designed to encourage transparency and maintain a... - Source: dev.to / 2 months ago
  • Apache Hadoop: Pioneering Open Source Innovation in Big Data
    Apache Hadoop is more than just software—it’s a full-fledged ecosystem built on the principles of open collaboration and decentralized governance. Born out of a need to process vast amounts of information efficiently, Hadoop uses a distributed file system and the MapReduce programming model to enable scalable, fault-tolerant computing. Central to its success is a diverse ecosystem that includes influential... - Source: dev.to / 3 months ago
View more

Ansible mentions (9)

  • Mentorship Group
    We are open to practice using any open-source project, however, we want to set a sharp focus on projects maintained by the Red Hat, and our own projects in the Caravana Cloud organization on github. If there is no reason to do differently, we'll build using technologies such as OpenShift, Quarkus, Ansible and related projects. - Source: dev.to / almost 2 years ago
  • Observability Mythbusters: Yes, Observability-Landscape-as-Code is a Thing
    *Codifying the deployment of the OTel Collector *(to Nomad, Kubernetes, or a VM) using tools such as Terraform, Pulumi, or Ansible. The Collector funnels your OTel data to your Observability back-end. ✅. - Source: dev.to / almost 3 years ago
  • Maintenance mode - vmware.vmware_rest Ansible collection
    Most of what I've learnt today was purley from this blog and only because it's from ansible.com - dated now I guess ... Source: almost 3 years ago
  • Proactive Kubernetes Monitoring with Alerting
    I installed the helm release using Ansible, but you can install with the following helm commands:. - Source: dev.to / almost 3 years ago
  • Cannot run a playbook in crontab - Python error
    [root@ansible ~]# pip show ansible Name: ansible Version: 2.9.25 Summary: Radically simple IT automation Home-page: https://ansible.com/ Author: Ansible, Inc. Author-email: info@ansible.com License: GPLv3+ Location: /usr/lib/python2.7/site-packagesRequires: jinja2, PyYAML, cryptography Required-by:. Source: over 3 years ago
View more

What are some alternatives?

When comparing Hadoop and Ansible, you can also consider the following products

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

Chef - Automation for all of your technology. Overcome the complexity and rapidly ship your infrastructure and apps anywhere with automation.

Apache Storm - Apache Storm is a free and open source distributed realtime computation system.

Jenkins - Jenkins is an open-source continuous integration server with 300+ plugins to support all kinds of software development

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

Codeship - Codeship is a fast and secure hosted Continuous Delivery platform that scales with your needs.

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