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Qubole VS Google Cloud Dataproc

Compare Qubole VS Google Cloud Dataproc and see what are their differences

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Qubole logo Qubole

Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
  • Qubole Landing page
    Landing page //
    2023-06-22
  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09

Qubole videos

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Fast and Cost Effective Machine Learning Deployment with S3, Qubole, and Spark

More videos:

  • Review - Migrating Big Data to the Cloud: WANdisco, GigaOM and Qubole
  • Review - Democratizing Data with Qubole

Google Cloud Dataproc videos

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Dataproc

Category Popularity

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

Qubole

Google Cloud Dataproc

Data Dashboard
38 38%
Data Dashboard
62% 62
Big Data
45 45%
Big Data
55% 55
Data Warehousing
59 59%
Data Warehousing
41% 41
Development
0 0%
Development
100% 100

User comments

Share your experience with using Qubole 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.

Qubole mentions (0)

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

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

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

MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming

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

Snowflake - Snowflake is the only data platform built for the cloud for all your data & all your users. Learn more about our purpose-built SQL cloud data warehouse.

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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