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Amazon EMR VS MyAnalytics

Compare Amazon EMR VS MyAnalytics and see what are their differences

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Amazon EMR logo Amazon EMR

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

MyAnalytics logo MyAnalytics

MyAnalytics, now rebranded to Microsoft Viva Insights, is a customizable suite of tools that integrates with Office 365 to drive employee engagement and increase productivity.
  • Amazon EMR Landing page
    Landing page //
    2023-04-02
  • MyAnalytics Landing page
    Landing page //
    2023-09-21

Amazon EMR videos

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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

MyAnalytics videos

No MyAnalytics videos yet. You could help us improve this page by suggesting one.

+ Add video

Category Popularity

0-100% (relative to Amazon EMR and MyAnalytics)

Amazon EMR

MyAnalytics

Data Dashboard
91 91%
Data Dashboard
9% 9
Technical Computing
0 0%
Technical Computing
100% 100
Big Data
100 100%
Big Data
0% 0
Business & Commerce
0 0%
Business & Commerce
100% 100

User comments

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Social recommendations and mentions

Based on our record, Amazon EMR seems to be more popular. 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.

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: about 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: almost 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: almost 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
View more

MyAnalytics mentions (0)

We have not tracked any mentions of MyAnalytics yet. Tracking of MyAnalytics recommendations started around Mar 2022.

What are some alternatives?

When comparing Amazon EMR and MyAnalytics, you can also consider the following products

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

Arcadia Enterprise - Arcadia Enterprise is the ultimate native BI for data lakes with real-time streaming visualizations, all without adding hardware or moving data.

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

Azure Databricks - Azure Databricks is a fast, easy, and collaborative Apache Spark-based big data analytics service designed for data science and data engineering.

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

GraphPad Prism - Overview. GraphPad Prism, available for both Windows and Mac computers, combines scientific graphing, comprehensive curve fitting (nonlinear regression), understandable statistics, and data organization.

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