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GridGain In-Memory Data Fabric VS Google Cloud Dataproc

Compare GridGain In-Memory Data Fabric VS Google Cloud Dataproc and see what are their differences

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GridGain In-Memory Data Fabric logo GridGain In-Memory Data Fabric

TheGridGain In-Memory Computing Platform is a comprehensive solution provides speed and scale for data intensive applications across any data store

Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
  • GridGain In-Memory Data Fabric Landing page
    Landing page //
    2023-05-09
  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09

GridGain In-Memory Data Fabric videos

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Deploying the GridGain In-Memory Data Fabric

Google Cloud Dataproc videos

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Dataproc

Category Popularity

0-100% (relative to GridGain In-Memory Data Fabric and Google Cloud Dataproc)

GridGain In-Memory Data Fabric

Google Cloud Dataproc

Data Dashboard
29 29%
Data Dashboard
71% 71
Business Intelligence
100 100%
Business Intelligence
0% 0
Big Data
0 0%
Big Data
100% 100
Data Visualization
100 100%
Data Visualization
0% 0

User comments

Share your experience with using GridGain In-Memory Data Fabric 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.

GridGain In-Memory Data Fabric mentions (0)

We have not tracked any mentions of GridGain In-Memory Data Fabric yet. Tracking of GridGain In-Memory Data Fabric 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 GridGain In-Memory Data Fabric and Google Cloud Dataproc, you can also consider the following products

Pentaho - Pentaho is a Business Intelligence software company that offers Pentaho Business Analytics, a suite...

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

JasperReports - JasperReports Server is a stand-alone and embeddable reporting server.

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

SharpDevelop Reports - SharpDevelop Reports (SDR) is the open source .NET reporting solution shipping with ...

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

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