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Apache Oozie VS Google Cloud Dataflow

Compare Apache Oozie VS Google Cloud Dataflow and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Apache Oozie logo Apache Oozie

Apache Oozie Workflow Scheduler for Hadoop

Google Cloud Dataflow logo Google Cloud Dataflow

Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
  • Apache Oozie Landing page
    Landing page //
    2021-07-25
  • Google Cloud Dataflow Landing page
    Landing page //
    2023-10-03

Apache Oozie videos

+ Add

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

Google Cloud Dataflow videos

+ Add

Introduction to Google Cloud Dataflow - Course Introduction

More videos:

  • Review - Serverless data processing with Google Cloud Dataflow (Google Cloud Next '17)
  • Review - Apache Beam and Google Cloud Dataflow

Category Popularity

0-100% (relative to Apache Oozie and Google Cloud Dataflow)

Apache Oozie

Google Cloud Dataflow

Workflow Automation
100 100%
Workflow Automation
0% 0
Big Data
0 0%
Big Data
100% 100
IT Automation
100 100%
IT Automation
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100

User comments

Share your experience with using Apache Oozie and Google Cloud Dataflow. For example, how are they different and which one is better?
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Reviews

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

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

Google Cloud Dataflow Reviews

Top 8 Apache Airflow Alternatives in 2024
Google Cloud Dataflow is highly focused on real-time streaming data and batch data processing from web resources, IoT devices, etc. Data gets cleansed and filtered as Dataflow implements Apache Beam to simplify large-scale data processing. Such prepared data is ready for analysis for Google BigQuery or other analytics tools for prediction, personalization, and other purposes.
Source: blog.skyvia.com

Social recommendations and mentions

Based on our record, Google Cloud Dataflow seems to be a lot more popular than Apache Oozie. While we know about 14 links to Google Cloud Dataflow, we've tracked only 1 mention of Apache Oozie. 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 Oozie mentions (1)

Google Cloud Dataflow mentions (14)

  • How do you implement CDC in your organization
    Imo if you are using the cloud and not doing anything particularly fancy the native tooling is good enough. For AWS that is DMS (for RDBMS) and Kinesis/Lamba (for streams). Google has Data Fusion and Dataflow . Azure hasData Factory if you are unfortunate enough to have to use SQL Server or Azure. Imo the vendored tools and open source tools are more useful when you need to ingest data from SaaS platforms, and... Source: about 1 year ago
  • Here’s a playlist of 7 hours of music I use to focus when I’m coding/developing. Post yours as well if you also have one!
    This sub is for Apache Beam and Google Cloud Dataflow as the sidebar suggests. Source: over 1 year ago
  • How are view/listen counts rolled up on something like Spotify/YouTube?
    I am pretty sure they are using pub/sub with probably a Dataflow pipeline to process all that data. Source: over 1 year ago
  • Best way to export several GCP datasets to AWS?
    You can run a Dataflow job that copies the data directly from BQ into S3, though you'll have to run a job per table. This can be somewhat expensive to do. Source: over 1 year ago
  • Why we don’t use Spark
    It was clear we needed something that was built specifically for our big-data SaaS requirements. Dataflow was our first idea, as the service is fully managed, highly scalable, fairly reliable and has a unified model for streaming & batch workloads. Sadly, the cost of this service was quite large. Secondly, at that moment in time, the service only accepted Java implementations, of which we had little knowledge... - Source: dev.to / almost 2 years ago
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What are some alternatives?

When comparing Apache Oozie and Google Cloud Dataflow, you can also consider the following products

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

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

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

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

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.

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

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