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Teradata QueryGrid VS Google Cloud Dataproc

Compare Teradata QueryGrid VS Google Cloud Dataproc and see what are their differences

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

Teradata QueryGrid logo Teradata QueryGrid

Data Fabric

Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
  • Teradata QueryGrid Landing page
    Landing page //
    2023-08-20
  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09

Teradata QueryGrid videos

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Google Cloud Dataproc videos

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Dataproc

Category Popularity

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

Teradata QueryGrid

Google Cloud Dataproc

Data Dashboard
26 26%
Data Dashboard
74% 74
Data Integration
100 100%
Data Integration
0% 0
Big Data
0 0%
Big Data
100% 100
AI Platform
100 100%
AI Platform
0% 0

User comments

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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.

Teradata QueryGrid mentions (0)

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

Denodo - Denodo delivers on-demand real-time data access to many sources as integrated data services with high performance using intelligent real-time query optimization, caching, in-memory and hybrid strategies.

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

IBM Cloud Pak for Data - Move to cloud faster with IBM Cloud Paks running on Red Hat OpenShift – fully integrated, open, containerized and secure solutions certified by IBM.

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

data.world - The social network for data people

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

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