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Mercurial SCM VS Google Cloud Dataproc

Compare Mercurial SCM VS Google Cloud Dataproc and see what are their differences

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Contents:
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  2. » Videos
  3. » Reviews
  4. » Alternatives

Mercurial SCM logo Mercurial SCM

Mercurial is a free, distributed source control management tool.

Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
  • Mercurial SCM Landing page
    Landing page //
    2021-10-17
  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09

Mercurial SCM videos

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Google Cloud Dataproc videos

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Dataproc

Category Popularity

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

Mercurial SCM

Google Cloud Dataproc

Git
100 100%
Git
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Code Collaboration
100 100%
Code Collaboration
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

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Social recommendations and mentions

Based on our record, Google Cloud Dataproc should be more popular than Mercurial SCM. 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.

Mercurial SCM mentions (2)

  • Why so rude?
    Many people have asked me to write a blog post on my preference of Mercurial over Git and so far I've refused and will continue doing so for the foreseeable future. - Source: dev.to / 4 months ago
  • Mercurial Paris Conference will take place on April 05-07 2023 in Paris France. Call for papers are open!
    Mercurial Paris Conference 2023 is a professional and technical conference around mercurial scm, a free, distributed source control management tool. Source: over 1 year ago

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 Mercurial SCM and Google Cloud Dataproc, you can also consider the following products

Git - Git is a free and open source version control system designed to handle everything from small to very large projects with speed and efficiency. It is easy to learn and lightweight with lighting fast performance that outclasses competitors.

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

GitHub Desktop - GitHub Desktop is a seamless way to contribute to projects on GitHub and GitHub Enterprise.

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

Atlassian Bitbucket Server - Atlassian Bitbucket Server is a scalable collaborative Git solution.

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

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