Apache Oozie
Apache Oozie

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Apache Spark
Apache Spark

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Apache Oozie vs Apache Spark: 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, *Apache Spark** is detailed as "Fast and general engine for large-scale data processing". 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.

Apache Oozie and Apache Spark are primarily classified as "Workflow Manager" and "Big Data" tools respectively.

Apache Spark is an open source tool with 22.9K GitHub stars and 19.7K GitHub forks. Here's a link to Apache Spark's open source repository on GitHub.

According to the StackShare community, Apache Spark has a broader approval, being mentioned in 356 company stacks & 564 developers stacks; compared to Apache Oozie, which is listed in 8 company stacks and 5 developer stacks.

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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 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.

Want advice about which of these to choose?Ask the StackShare community!

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      What tools integrate with Apache Oozie?
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        What are some alternatives to Apache Oozie and Apache Spark?
        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 Beam
        It implements batch and streaming data processing jobs that run on any execution engine. It executes pipelines on multiple execution environments.
        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.
        Camunda
        It is an open source platform for workflow and decision automation that brings business users and software developers together.
        Zenaton
        It is a toolset for developers and data engineers to run and monitor data processes and asynchronous jobs. It makes it really easy and helps developers to programmatically build, run and scale long-running and distributed workflows.
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        Decisions about Apache Oozie and Apache Spark
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        Reviews of Apache Oozie and Apache Spark
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        How developers use Apache Oozie and Apache Spark
        Avatar of Wei Chen
        Wei Chen uses Apache SparkApache Spark

        Spark is good at parallel data processing management. We wrote a neat program to handle the TBs data we get everyday.

        Avatar of Ralic Lo
        Ralic Lo uses Apache SparkApache Spark

        Used Spark Dataframe API on Spark-R for big data analysis.

        Avatar of Kalibrr
        Kalibrr uses Apache SparkApache Spark

        We use Apache Spark in computing our recommendations.

        Avatar of BrainFinance
        BrainFinance uses Apache SparkApache Spark

        As a part of big data machine learning stack (SMACK).

        Avatar of Dotmetrics
        Dotmetrics uses Apache SparkApache Spark

        Big data analytics and nightly transformation jobs.

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