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Cloud Dataprep VS Google Cloud Dataproc

Compare Cloud Dataprep VS Google Cloud Dataproc and see what are their differences

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Cloud Dataprep logo Cloud Dataprep

Cloud Dataprep by Trifacta is a data prep & cleansing service for exploring, cleaning & preparing datasets using a simple drag & drop browser environment

Google Cloud Dataproc logo Google Cloud Dataproc

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

Cloud Dataprep videos

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Cloud Dataprep Tutorial - Getting Started 101

More videos:

  • Review - Advanced Data Cleanup Techniques using Cloud Dataprep (Cloud Next '19)
  • Demo - Google Cloud Dataprep Premium product demo

Google Cloud Dataproc videos

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Dataproc

Category Popularity

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

Cloud Dataprep

Google Cloud Dataproc

Office & Productivity
100 100%
Office & Productivity
0% 0
Data Dashboard
24 24%
Data Dashboard
76% 76
Development
53 53%
Development
47% 47
Big Data
0 0%
Big Data
100% 100

User comments

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

Google Cloud Dataproc might be a bit more popular than Cloud Dataprep. We know about 3 links to it since March 2021 and only 3 links to Cloud Dataprep. 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.

Cloud Dataprep mentions (3)

  • How to upload large excel-sheet file (90MB) to BigQuery
    Check Google Cloud Dataprep – requires no coding, you can normalize & clean up the data as well. I've done this many times, saved me headaches from dirty data in Excel files. Source: almost 2 years ago
  • Data mapping process
    Not sure if I understand the request but a commercial tool I know of is https://cloud.google.com/dataprep - it sounds like that could be helpful but I am not sure. Source: over 2 years ago
  • The beginner GCP user seeking some help from the experts.
    If you need to adjust the underlying data, you can use Cloud Dataprep to do manipulations (here). Source: about 3 years ago

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 / almost 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: about 2 years ago

What are some alternatives?

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

Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.

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

GeoSpock - GeoSpock is the platform for data lake management, providing a unified view of the data assets within an organization and making it easily accessible.

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

Delta Lake - Application and Data, Data Stores, and Big Data Tools

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

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