Software Alternatives, Accelerators & Startups

Apache Ambari VS Apache Karaf

Compare Apache Ambari VS Apache Karaf and see what are their differences

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Apache Ambari logo Apache Ambari

Ambari is aimed at making Hadoop management simpler by developing software for provisioning, managing, and monitoring Hadoop clusters.

Apache Karaf logo Apache Karaf

Apache Karaf is a lightweight, modern and polymorphic container powered by OSGi.
  • Apache Ambari Landing page
    Landing page //
    2023-01-08
  • Apache Karaf Landing page
    Landing page //
    2021-07-29

Apache Ambari features and specs

  • Centralized Management
    Apache Ambari provides a centralized platform to manage, monitor, and provision Hadoop clusters efficiently. This feature simplifies the administration tasks by offering a single interface for managing cluster operations.
  • User-Friendly Interface
    Ambari offers a graphical user interface (GUI) that is intuitive and easy to use, enabling administrators to manage clusters without requiring extensive command-line knowledge.
  • Automated Installation
    It supports automated installation and configuration of Hadoop components, reducing the complexity and time required to set up a cluster.
  • Real-time Monitoring
    Ambari provides real-time insights into cluster health and performance through a variety of metrics and dashboards, allowing for proactive management.
  • Extensibility
    The platform is designed to be extensible, allowing developers to write custom alerts and metrics, thus adapting the system to meet specific needs.

Possible disadvantages of Apache Ambari

  • Resource Intensive
    Ambari can consume significant system resources, especially in larger clusters, which could impact performance if resources are not adequately provisioned.
  • Limited Support for Non-Hadoop Ecosystems
    The primary focus of Apache Ambari is on Hadoop ecosystems, and it lacks extensive support for non-Hadoop big data technologies, which can limit its applicability in heterogeneous environments.
  • Complexity for Small Clusters
    For smaller Hadoop deployments, the use of Ambari might be overkill and add unnecessary complexity due to its comprehensive nature.
  • Dependency on Updates
    Users can encounter compatibility issues or bugs following updates, which can require troubleshooting and delay important operations.
  • Steep Learning Curve for Customization
    While it is extensible, customization in Ambari can have a steep learning curve, demanding deeper technical knowledge to implement specific configurations or custom components.

Apache Karaf features and specs

  • Modular architecture
    Apache Karaf features a highly modular architecture that allows users to deploy, control, and monitor applications in a flexible and efficient manner. This makes it easy to manage dependencies and extend functionalities as needed.
  • OSGi support
    Karaf fully supports OSGi (Open Services Gateway initiative), which is a framework for developing and deploying modular software programs and libraries. This enables dynamic updates and replacement of modules without requiring a system restart.
  • Extensible and flexible
    Karaf's extensible architecture allows developers to integrate various technologies and custom modules, fostering a flexible environment that can suit a wide range of application types and requirements.
  • Enterprise features
    It provides a range of enterprise-ready features such as hot deployment, dynamic configuration, clustering, and high availability, which can help in building robust and scalable applications.
  • Comprehensive tooling
    Karaf comes with comprehensive tooling support including a powerful CLI, web console, and various tools for monitoring and managing the runtime environment. These tools simplify everyday management tasks.

Possible disadvantages of Apache Karaf

  • Steeper learning curve
    Due to its modular and extensible nature, Apache Karaf can have a steeper learning curve for new users, especially those unfamiliar with OSGi concepts and enterprise middleware.
  • Resource intensity
    Running and managing an Apache Karaf instance can be resource-intensive, especially when dealing with large-scale or highly modular applications. Adequate memory and processing power are required to maintain optimal performance.
  • Complex deployment
    While Karaf can handle complex deployment scenarios, setting it up and configuring it properly can be more involved compared to other simpler solutions. This complexity can increase the initial setup time and effort.
  • Limited community support
    Despite being an Apache project, the community around Apache Karaf might not be as large or active as other popular frameworks, potentially making it harder to find ample resources or immediate support.
  • Dependency management challenges
    Managing dependencies in Karaf, especially when dealing with multiple third-party libraries and their versions, can become cumbersome and lead to conflicts if not handled carefully.

Apache Ambari videos

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Apache Karaf videos

EIK - How to use Apache Karaf inside of Eclipse

More videos:

  • Review - OpenDaylight's Apache Karaf Report- Jamie Goodyear

Category Popularity

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Cloud Computing
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Development
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Cloud Hosting
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User comments

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Social recommendations and mentions

Apache Karaf might be a bit more popular than Apache Ambari. We know about 1 link to it since March 2021 and only 1 link to Apache Ambari. 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.

Apache Ambari mentions (1)

  • In One Minute : Hadoop
    Ambari, A web-based tool for provisioning, managing, and monitoring Apache Hadoop clusters which includes support for Hadoop HDFS, Hadoop MapReduce, Hive, HCatalog, HBase, ZooKeeper, Oozie, Pig and Sqoop. Ambari also provides a dashboard for viewing cluster health such as heatmaps and ability to view MapReduce, Pig and Hive applications visually along with features to diagnose their performance characteristics in... - Source: dev.to / over 2 years ago

Apache Karaf mentions (1)

  • Need advice: Java Software Architecture for SaaS startup doing CRUD and REST APIs?
    Apache Karaf with OSGi works pretty nice using annotation based dependency injection with the declarative services, removing the need to mess with those hopefully archaic XML blueprints. Too bad it's not as trendy as spring and the developers so many of the tutorials can be a bit dated and hard to find. Karaf also supports many other frameworks and programming models as well and there's even Red Hat supported... Source: about 4 years ago

What are some alternatives?

When comparing Apache Ambari and Apache Karaf, you can also consider the following products

Apache HBase - Apache HBase – Apache HBase™ Home

Docker - Docker is an open platform that enables developers and system administrators to create distributed applications.

Apache Mahout - Distributed Linear Algebra

Google App Engine - A powerful platform to build web and mobile apps that scale automatically.

Apache Pig - Pig is a high-level platform for creating MapReduce programs used with Hadoop.

rkt - App Container runtime