Software Alternatives, Accelerators & Startups

Apache Ambari VS Apache Oozie

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

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Apache Ambari logo Apache Ambari

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

Apache Oozie logo Apache Oozie

Apache Oozie Workflow Scheduler for Hadoop
  • Apache Ambari Landing page
    Landing page //
    2023-01-08
  • Apache Oozie Landing page
    Landing page //
    2021-07-25

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 Oozie features and specs

  • Integration
    Apache Oozie is well-integrated with the Hadoop ecosystem, allowing it to schedule jobs across various components like Hive, Pig, Sqoop, and MapReduce. This makes it highly beneficial for users working in Hadoop environments.
  • Flexibility
    Oozie supports various job types and offers workflow orchestration capabilities which go beyond simple job scheduling, including decision paths, sub-workflows, and the ability to execute arbitrary shell scripts.
  • Extensibility
    It is highly extensible, allowing users to add custom action nodes in workflows. This extends its functionality beyond built-in support, accommodating more complex data processing needs.
  • Dependency Management
    Oozie provides ways to manage job dependencies, which is crucial for executing data pipelines where the output of one job may serve as the input for another.
  • Time and Event-based Triggering
    It supports both time-based and event-based triggering of workflows, which provides flexibility in how and when workflows are initiated according to specific business requirements.

Possible disadvantages of Apache Oozie

  • Complexity
    Oozie's configuration and operation can be complex, requiring a steep learning curve for newcomers, especially those unfamiliar with XML-based configuration.
  • Limited User Interface
    Compared to other modern workflow scheduling tools, Oozie's UI is considered less intuitive and user-friendly, making it more challenging for users to manage and monitor workflows.
  • Scalability Issues
    For large-scale data processing, Oozie may face performance bottlenecks and scalability issues, especially when dealing with a vast number of concurrent workflows.
  • Lack of Advanced Features
    Oozie lacks some advanced features offered by newer workflow management tools, such as easy integration with modern DevOps practices, advanced failure handling, and sophisticated monitoring capabilities.
  • Resource Management
    Oozie does not offer built-in resource management, relying heavily on external tools and configurations to manage resources effectively, which can complicate workflow setups in resource-constrained environments.

Apache Ambari videos

No Apache Ambari videos yet. You could help us improve this page by suggesting one.

Add video

Apache Oozie videos

Migrating Apache Oozie Workflows to Apache Airflow

More videos:

  • Review - Breathing New Life into Apache Oozie with Apache Ambari Workflow Manager
  • Review - Breathing New Life into Apache Oozie with Apache Ambari Workflow Manager

Category Popularity

0-100% (relative to Apache Ambari and Apache Oozie)
Data Dashboard
100 100%
0% 0
Workflow Automation
0 0%
100% 100
Development
100 100%
0% 0
IT Automation
0 0%
100% 100

User comments

Share your experience with using Apache Ambari and Apache Oozie. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Ambari and Apache Oozie

Apache Ambari Reviews

We have no reviews of Apache Ambari yet.
Be the first one to post

Apache Oozie Reviews

10 Best Airflow Alternatives for 2024
One of the workflow scheduler services/applications operating on the Hadoop cluster is Apache Oozie. It is used to handle Hadoop tasks such as Hive, Sqoop, SQL, MapReduce, and HDFS operations such as distcp. It is a system that manages the workflow of jobs that are reliant on each other. Users can design Directed Acyclic Graphs of processes here, which can be performed in...
Source: hevodata.com

Social recommendations and mentions

Apache Oozie 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 Oozie mentions (1)

What are some alternatives?

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

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

Control-M - Control‑M simplifies and automates diverse batch application workloads while reducing failure rates, improving SLAs, and accelerating application deployment.

Apache HBase - Apache HBase – Apache HBase™ Home

Stonebranch - Stonebranch builds IT orchestration and automation solutions that transform business IT environments from simple IT task automation into sophisticated, real-time business service automation.

Apache Mahout - Distributed Linear Algebra

ActiveBatch - Orchestrate the entire tech stack with ActiveBatch Workload Automation & Job Scheduling. Build and manage workflows from one place.