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AWStats VS Amazon EMR

Compare AWStats VS Amazon EMR and see what are their differences

AWStats logo AWStats

AWStats is a Open Source Web Analytics software written in Perl.

Amazon EMR logo Amazon EMR

Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
  • AWStats Landing page
    Landing page //
    2021-10-15
  • Amazon EMR Landing page
    Landing page //
    2023-04-02

AWStats videos

Traffic Stats Comparison: Google Analytics vs CPanel AWSTATS vs Webalizer vs Analog Stats

More videos:

  • Tutorial - AWStats Web Stats - HOW TO READ Your Website Traffic Statistics
  • Tutorial - CPanel Tutorial - How to Use AWSTATS to Check Web Traffic

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 AWStats and Amazon EMR)
Analytics
100 100%
0% 0
Data Dashboard
0 0%
100% 100
Web Analytics
100 100%
0% 0
Big Data
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare AWStats and Amazon EMR

AWStats Reviews

Top 5 open source alternatives to Google Analytics
Web server log files provide a rich vein of information about visitors to your site, but tapping into that vein isn't always easy. That's where AWStats comes to the rescue. While it lacks the most modern look and feel, AWStats more than makes up for that with breadth of data it can present.
Source: opensource.com

Amazon EMR Reviews

We have no reviews of Amazon EMR yet.
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Social recommendations and mentions

Based on our record, Amazon EMR should be more popular than AWStats. 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.

AWStats mentions (3)

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: 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: 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 AWStats and Amazon EMR, you can also consider the following products

Google Analytics - Improve your website to increase conversions, improve the user experience, and make more money using Google Analytics. Measure, understand and quantify engagement on your site with customized and in-depth reports.

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

Matomo - Matomo is an open-source web analytics platform

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

Open Web Analytics - Open Web Analytics - Web Analytics – Open Source Web Analytics Framework

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