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Apache Oozie
Apache Oozie

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Workfront
Workfront

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Apache Oozie vs Workfront: What are the differences?

Developers describe Apache Oozie as "An open-source workflow scheduling system *". It is a server-based workflow scheduling system to manage Hadoop jobs. Workflows in it are defined as a collection of control flow and action nodes in a directed acyclic graph. Control flow nodes define the beginning and the end of a workflow as well as a mechanism to control the workflow execution path. On the other hand, *Workfront** is detailed as "A platform for enterprise work management". It allows user to manage projects in one place. It helps marketing, IT, & enterprise teams conquer chaos by improving productivity, collaboration, and visibility.

Apache Oozie and Workfront can be categorized as "Workflow Manager" tools.

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What is Apache Oozie?

It is a server-based workflow scheduling system to manage Hadoop jobs. Workflows in it are defined as a collection of control flow and action nodes in a directed acyclic graph. Control flow nodes define the beginning and the end of a workflow as well as a mechanism to control the workflow execution path.

What is Workfront?

It allows user to manage projects in one place. It helps marketing, IT, & enterprise teams conquer chaos by improving productivity, collaboration, and visibility.
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            What are some alternatives to Apache Oozie and Workfront?
            Apache Spark
            Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
            Airflow
            Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
            Apache NiFi
            An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.
            Yarn
            Yarn caches every package it downloads so it never needs to again. It also parallelizes operations to maximize resource utilization so install times are faster than ever.
            Luigi
            It is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
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