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Cloudera CDH VS Google Cloud Dataproc

Compare Cloudera CDH VS Google Cloud Dataproc and see what are their differences

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Cloudera CDH logo Cloudera CDH

Imagine what your business could do if all your data were collected in one centralized, secure, fully-governed place that any department could access anytime.

Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
  • Cloudera CDH Landing page
    Landing page //
    2023-10-15
  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09

Cloudera CDH videos

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Introduction

Google Cloud Dataproc videos

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Dataproc

Category Popularity

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

Cloudera CDH

Google Cloud Dataproc

Big Data
27 27%
Big Data
73% 73
Data Dashboard
19 19%
Data Dashboard
81% 81
Development
27 27%
Development
73% 73
Database Tools
100 100%
Database Tools
0% 0

User comments

Share your experience with using Cloudera CDH 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.

Cloudera CDH mentions (0)

We have not tracked any mentions of Cloudera CDH yet. Tracking of Cloudera CDH 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 / 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 Cloudera CDH and Google Cloud Dataproc, you can also consider the following products

Platfora - BI and Analytics Platform

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

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

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

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

SingleStore - SingleStore DB is a high-performance SQL compliant relational database management tool that offers data processing, ingesting, and transaction processing.

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