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Apache Oozie vs Zookeeper: What are the differences?

Introduction

Apache Oozie and Apache ZooKeeper are both widely used open-source distributed coordination and workflow management systems. Although they serve different purposes, they have some key differences that set them apart.

  1. Workflow and Coordination vs. Distributed Configuration Management Apache Oozie primarily focuses on workflow and coordination. It allows users to define and manage complex workflows, including dependencies between actions, in order to automate and coordinate various data processing tasks across a Hadoop cluster. On the other hand, Apache ZooKeeper is a distributed coordination service that provides a reliable and fault-tolerant way to store and manage configuration information, naming, synchronization, and group services across a cluster.

  2. Workflow Management vs. Distributed Consensus Oozie provides workflow management capabilities by allowing users to define and execute a series of actions in a specific order while supporting control flows and decision points. On the contrary, ZooKeeper is designed to provide distributed consensus, enabling multiple distributed systems to agree on a consistent view of their shared state. It achieves this by implementing the ZooKeeper atomic broadcast protocol, offering strong consistency guarantees.

  3. Dependency Management vs. Hierarchical Namespace In Oozie, users can define dependencies between different actions within a workflow, ensuring that actions are executed in the correct order. This makes it easier to handle complex workflows with interdependent tasks. In contrast, ZooKeeper provides a hierarchical namespace, similar to a file system, where data is organized in a tree-like structure. Each node in the tree can have associated data, and ZooKeeper watches can be set on nodes to receive notifications when the data changes.

  4. Centralized vs. Decentralized Architecture Oozie follows a centralized architecture, where a single Oozie server manages the coordination, scheduling, and execution of workflows. Clients submit jobs to the Oozie server for execution, and the server handles the coordination among various tasks and their dependencies. On the other hand, ZooKeeper follows a decentralized architecture, where multiple ZooKeeper servers form an ensemble and work together to provide fault tolerance and high availability. Clients interact with any of the servers to access the shared data.

  5. Built-in Scheduling vs. Event-driven Notifications Oozie provides built-in scheduling capabilities, allowing users to define when and at what frequency their workflows should run. This makes it convenient for managing recurring data processing tasks. In contrast, ZooKeeper does not provide built-in scheduling capabilities. It focuses on event-driven notifications, allowing clients to receive notifications when certain changes occur in the ZooKeeper data tree, helping them react to those changes effectively.

  6. Higher-level Abstraction vs. Low-level Primitive Operations Oozie offers a higher-level workflow abstraction, allowing users to define and manage complex workflows using a workflow definition language or graphical user interface. This abstracts away the underlying details of task coordination and control flow, making it easier for users to work with complex workflows. On the other hand, ZooKeeper offers low-level primitive operations, such as creating, updating, and deleting nodes and managing watches, providing a simpler interface for distributed coordination primitives.

In summary, Apache Oozie focuses on workflow management and coordination, supporting complex dependencies and providing built-in scheduling capabilities, while Apache ZooKeeper focuses on distributed coordination and provides a hierarchical namespace with event-driven notifications, using a decentralized architecture.

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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
      Curator
    • 2
      Used in ClickHouse
    • 2
      Supports DC/OS
    • 1
      Used in Hadoop
    • 1
      Embeddable In Java Service

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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 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.
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