Software Alternatives, Accelerators & Startups

Mercurial SCM VS Amazon EMR

Compare Mercurial SCM VS Amazon EMR and see what are their differences

Mercurial SCM logo Mercurial SCM

Mercurial is a free, distributed source control management tool.

Amazon EMR logo Amazon EMR

Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
  • Mercurial SCM Landing page
    Landing page //
    2021-10-17
  • Amazon EMR Landing page
    Landing page //
    2023-04-02

Mercurial SCM videos

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Amazon EMR videos

Amazon EMR Masterclass

More videos:

  • Review - Deep Dive into What’s New in Amazon EMR - AWS Online Tech Talks
  • Tutorial - How to use Apache Hive and DynamoDB using Amazon EMR

Category Popularity

0-100% (relative to Mercurial SCM and Amazon EMR)
Git
100 100%
0% 0
Data Dashboard
0 0%
100% 100
Code Collaboration
100 100%
0% 0
Big Data
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Amazon EMR should be more popular than Mercurial SCM. It has been mentiond 10 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

Amazon EMR mentions (10)

  • 5 Best Practices For Data Integration To Boost ROI And Efficiency
    There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: over 1 year ago
  • What compute service i should use? Advice for a duck-tape kind of guy
    I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: about 2 years ago
  • Processing a large text file containing millions of records.
    This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: about 2 years ago
  • How to use Spark and Pandas to prepare big data
    Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 2 years ago
  • Beginner building a Hadoop cluster
    Check out https://aws.amazon.com/emr/. Source: about 2 years ago
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What are some alternatives?

When comparing Mercurial SCM and Amazon EMR, 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.

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

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

Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

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

Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost