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Google Cloud Dataproc VS Zeotap

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

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Contents:
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  2. » Videos
  3. » Reviews
  4. » Alternatives

Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost

Zeotap logo Zeotap

Zeotap is an extensive and reliable customer data platform that has been become the overnight sensation for business with versatile customer intelligence and identify resolution.
  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09
  • Zeotap Landing page
    Landing page //
    2023-10-23

Google Cloud Dataproc

Website
cloud.google.com
Release Date
-
Edit details

Zeotap

Website
zeotap.com
Release Date
2014 January
Startup details
Country
Germany
State
Berlin
City
Berlin
Founder(s)
Daniel Heer
Employees
100 - 249
Edit details

Google Cloud Dataproc videos

+ Add

Dataproc

Zeotap videos

+ Add

Zeotap: A short story about customer data

More videos:

  • Review - HCC Data & Tech #006 - Oliver Kanders, Zeotap

Category Popularity

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

Google Cloud Dataproc

Zeotap

Data Dashboard
100 100%
Data Dashboard
0% 0
Office & Productivity
0 0%
Office & Productivity
100% 100
Big Data
100 100%
Big Data
0% 0
Business & Commerce
0 0%
Business & Commerce
100% 100

User comments

Share your experience with using Google Cloud Dataproc and Zeotap. 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 should be more popular than Zeotap. 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.

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

Zeotap mentions (1)

  • New Spark Testing Utility - spark-property-tests
    We have open-sourced a small library - spark-property-tests for writing easy tests on spark dataframes. We have been using it internally at zeotap data engineering for some time now and thought that the community might benefit from it. Source: over 2 years ago

What are some alternatives?

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

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

BlueConic - BlueConic is a marketing platform that harnesses the data required to power the recognition of an individual at each interaction.

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

Ometria - Ometria is a predictive analytics and marketing platform built for retailers.

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

Simon Data - Simon Data enables businesses to effectively leverage all of their data to drive personalization and value for their customers.

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