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RapidMiner Studio VS Google Cloud Dataproc

Compare RapidMiner Studio VS Google Cloud Dataproc and see what are their differences

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

RapidMiner Studio logo RapidMiner Studio

Visual workflow designer for predictive analytics that brings data science and machine learning to everyone on the analytics team

Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
  • RapidMiner Studio Landing page
    Landing page //
    2022-07-03
  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09

RapidMiner Studio videos

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RapidMiner Studio in 60 Seconds | RapidMiner

Google Cloud Dataproc videos

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Dataproc

Category Popularity

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

RapidMiner Studio

Google Cloud Dataproc

Business & Commerce
100 100%
Business & Commerce
0% 0
Data Dashboard
10 10%
Data Dashboard
90% 90
Technical Computing
100 100%
Technical Computing
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using RapidMiner Studio 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.

RapidMiner Studio mentions (0)

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

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

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

IBM ILOG CPLEX Optimization Studio - IBM ILOG CPLEX Optimization Studio is an easy-to-use, affordable data analytics solution for businesses of all sizes who want to optimize their operations.

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

Pyramid Analytics - Pyramid Analytics provides business intelligence software that delivers data-driven insights for organizations with advanced analytics and data visualizations.

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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