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MapR Converged Data Platform VS Google Cloud Dataproc

Compare MapR Converged Data Platform VS Google Cloud Dataproc and see what are their differences

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MapR Converged Data Platform logo MapR Converged Data Platform

An enterprise-grade distributed data platform that you can trust to reliably store and process big and fast data.

Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
  • MapR Converged Data Platform Landing page
    Landing page //
    2022-10-08
  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09

MapR Converged Data Platform videos

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Lab Video Summary - MapR Converged Data Platform with MapR Streams

Google Cloud Dataproc videos

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Dataproc

Category Popularity

0-100% (relative to MapR Converged Data Platform and Google Cloud Dataproc)

MapR Converged Data Platform

Google Cloud Dataproc

Data Dashboard
32 32%
Data Dashboard
68% 68
Development
51 51%
Development
49% 49
Big Data
23 23%
Big Data
77% 77
File Management
100 100%
File Management
0% 0

User comments

Share your experience with using MapR Converged Data Platform 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.

MapR Converged Data Platform mentions (0)

We have not tracked any mentions of MapR Converged Data Platform yet. Tracking of MapR Converged Data Platform 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 MapR Converged Data Platform and Google Cloud Dataproc, 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.

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

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...

Mode - A complete analytical toolkit, free forever

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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