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Data Fabric VS Google Cloud Dataproc

Compare Data Fabric VS Google Cloud Dataproc and see what are their differences

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

Data Fabric logo Data Fabric

Data Fabric is an architecture and set of data services that provide consistent capabilities across a choice of endpoints spanning on-premises and multiple cloud environments.

Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
  • Data Fabric Landing page
    Landing page //
    2023-09-18
  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09

Data Fabric videos

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Data Fabric Explained

More videos:

  • Review - What is a data fabric?
  • Demo - Data Fabric Demonstration

Google Cloud Dataproc videos

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Dataproc

Category Popularity

0-100% (relative to Data Fabric and Google Cloud Dataproc)

Data Fabric

Google Cloud Dataproc

ETL
100 100%
ETL
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Developer Tools
100 100%
Developer Tools
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using Data Fabric and Google Cloud Dataproc. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Google Cloud Dataproc seems to be more popular. It has been mentiond 3 times since March 2021. 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.

Data Fabric mentions (0)

We have not tracked any mentions of Data Fabric yet. Tracking of Data Fabric recommendations started around Mar 2021.

Google Cloud Dataproc mentions (3)

  • Connecting IPython notebook to spark master running in different machines
    I have also a spark cluster created with google cloud dataproc. Source: about 1 year ago
  • Why we don’t use Spark
    Specifically, we heavily rely on managed services from our cloud provider, Google Cloud Platform (GCP), for hosting our data in managed databases like BigTable and Spanner. For data transformations, we initially heavily relied on DataProc - a managed service from Google to manage a Spark cluster. - Source: dev.to / about 2 years ago
  • Data processing issue
    With that, the best way to maximize processing and minimize time is to use Dataflow or Dataproc depending on your needs. These systems are highly parallel and clustered, which allows for much larger processing pipelines that execute quickly. Source: over 2 years ago

What are some alternatives?

When comparing Data Fabric and Google Cloud Dataproc, you can also consider the following products

Argo - Argo helps teams ask questions about their data from cloud services to make smarter, data-driven decisions.

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

Google Cloud Build - A fully managed continuous integration, delivery, & deployment platform that lets you build, test, and deploy in the cloud. Focus on coding by running fast, consistent, reliable automated builds.

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

Xplenty - Xplenty is the #1 SecurETL - allowing you to build low-code data pipelines on the most secure and flexible data transformation platform. No longer worry about manual data transformations. Start your free 14-day trial now.

HortonWorks Data Platform - The Hortonworks Data Platform is a 100% open source distribution of Apache Hadoop that is truly...

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