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Apache Oozie

40
69
+ 1
0
Zookeeper

619
866
+ 1
42
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Pros of Apache Oozie
Pros of Zookeeper
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    • 11
      High performance ,easy to generate node specific config
    • 8
      Java
    • 8
      Kafka support
    • 5
      Spring Boot Support
    • 3
      Supports extensive distributed IPC
    • 2
      Supports DC/OS
    • 2
      Used in ClickHouse
    • 1
      Curator
    • 1
      Embeddable In Java Service
    • 1
      Used in Hadoop

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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 Zookeeper?

    A centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services. All of these kinds of services are used in some form or another by distributed applications.

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    What companies use Apache Oozie?
    What companies use Zookeeper?
    See which teams inside your own company are using Apache Oozie or Zookeeper.
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    What tools integrate with Apache Oozie?
    What tools integrate with Zookeeper?
      No integrations found

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      What are some alternatives to Apache Oozie and Zookeeper?
      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.
      Apache Beam
      It implements batch and streaming data processing jobs that run on any execution engine. It executes pipelines on multiple execution environments.
      See all alternatives