Amazon EMR

Amazon EMR

Customer Verified
About TrustRadius Scoring
Score 8.5 out of 100
Amazon EMR (Elastic MapReduce)

Overview

Recent Reviews

Amazon EMR - fast, and elastic

7 out of 10
April 19, 2022
We use Amazon EMR (Elastic MapReduce) to run various types of algorithms related to health like calculation of body mass index, heart rate …
Continue reading

Amazon EMR Review

7 out of 10
September 22, 2020
Amazon EMR is being used by our organization to simplify running big data frameworks, and provide the Amazon EMR highlights, product …
Continue reading

Reviewer Pros & Cons

View all pros & cons

Video Reviews

Leaving a video review helps other professionals like you evaluate products. Be the first one in your network to record a review of Amazon EMR, and make your voice heard!

Pricing

View all pricing
N/A
Unavailable

What is Amazon EMR?

Amazon EMR is a cloud-native big data platform for processing vast amounts of data quickly, at scale. Using open source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi (Incubating), and Presto, coupled with the scalability of Amazon EC2 and scalable storage of Amazon…

Entry-level set up fee?

  • No setup fee

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting / Integration Services

Would you like us to let the vendor know that you want pricing?

Features Scorecard

No scorecards have been submitted for this product yet..

Product Details

What is Amazon EMR?

Amazon EMR is a cloud-native big data platform for processing vast amounts of data quickly, at scale. Using open source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi (Incubating), and Presto, coupled with the scalability of Amazon EC2 and scalable storage of Amazon S3, EMR gives analytical teams the engines and elasticity to run Petabyte-scale analysis.

Amazon EMR Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo

Comparisons

View all alternatives

Frequently Asked Questions

What is Amazon EMR?

Amazon EMR is a cloud-native big data platform for processing vast amounts of data quickly, at scale. Using open source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi (Incubating), and Presto, coupled with the scalability of Amazon EC2 and scalable storage of Amazon S3, EMR gives analytical teams the engines and elasticity to run Petabyte-scale analysis.

What is Amazon EMR's best feature?

Reviewers rate Support Rating highest, with a score of 9.

Who uses Amazon EMR?

The most common users of Amazon EMR are from Mid-sized Companies (51-1,000 employees) and the Computer Software industry.

Reviews and Ratings

 (57)

Ratings

Reviews

(1-20 of 20)
Companies can't remove reviews or game the system. Here's why
Score 8 out of 10
Vetted Review
Verified User
Review Source
You can use Amazon EMR if you wish to shift to the cloud and save money by using Apache Spark or Apache Hadoop on-premises. When the amount of work you have to handle data fluctuates a lot. Setting up flexible and scalable scenarios with AWS's EMR can assist you.
Score 7 out of 10
Vetted Review
Verified User
Review Source
Scenarios where it is good:
1. Where speed is important, and there is a vast amount of data to process
2. Configuration setup needs to be fast

Scenarios where it is not good:
1. For small companies which do not have enough money
2. For one-off uses, since the ramp up curve is high
Score 8 out of 10
Vetted Review
Verified User
Review Source
Amazon EMR is well suited in scenarios where
> You require Hadoop-based processing, and time is a constraint.
> Need a platform that supports Spark and Hive at the same time.
> Flexible resizing options are available - So it's a tool for conditions requiring an increase/decrease in cores. > Fast big data processing is a requirement.

I would look for other options if
> The job budget is limited, and time could be flexible
> Initialization (Starting the job) and Terminating the job require automatic interference (As with EMR, you will need to intervene manually).
Score 8 out of 10
Vetted Review
Verified User
Review Source
Our teams prefer using this service to deploy because it is simple to configure and scale even though it can be expensive at times. It also needs some training for new users to get familiar with all the functions and features. Experience matters a lot while using this platform.
José David Rodríguez Gómez | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
We are running it to perform preparation which takes a few hours on EC2 to be running on a spark-based EMR cluster to total the preparation inside minutes rather than a few hours. Ease of utilization and capacity to select from either Hadoop or spark. Processing time diminishes from 5-8 hours to 25-30 minutes compared with the Ec2 occurrence and more in a few cases.
Score 10 out of 10
Vetted Review
Verified User
Review Source
It provides a nice graphical user interface to manage and work with big data map reduction tasks instead of manual configuration with hadoop or cli.it saves a lot of time and effort.We create big data monitoring system filters.

It provides a good GUI to manage and handle big data map reduction tasks and its configuration saves a lot of time and effort.
Nick Waters | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Review Source
Amazon EMR (Elastic Map Reduce) is ideally suited for organisations that need to provide a scalable platform for data processing. Amazon EMR is perfect to handle data volumes of any size or volume and it is easy to configure and spin up an EMR cluster quickly. If you are cost-focused you need to be careful as an EMR cluster can end up costing a lot of money if misconfigured.
April 06, 2022

AWS has it all!

Jonathan Brotto | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
Review Source
When I need to process large data and meaningful information. But it is very flexible where I can scale based on the data size and how I want to analyze it. But still can improve for nontechnical users as there is some jargon to learn to get the most out of the solution.
Score 8 out of 10
Vetted Review
Verified User
Review Source
It has its use case. When it comes to extremely large datasets' pulling and transformation, it is the best way to do it. Just need to be aware that if something is not set correctly in the first place, the cost could potentially be very large. Therefore, it is very critical to not do development work there.
September 22, 2020

Amazon EMR Review

Score 7 out of 10
Vetted Review
Verified User
Review Source
Some scenarios where Amazon EMR is well suited include simplifying running big data frameworks, providing the Amazon EMR highlights, product details, and pricing information, and analyzing vast amounts of data. Some scenarios where Amazon EMR is less appropriate include assisting clients with problems on their servers, and coding our clients' many servers at our data centers.
Nicolas Costa Ossa | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Review Source
For example, when you have Apache Spark on-premise deployments, or also Apache Hadoop, and you want to move to the cloud and reduce costs, EMR is the right tool. When you have lots of ups and downs in workload levels to process data. AWS's EMR can help you by setting up flexible/scalable scenarios.
Score 8 out of 10
Vetted Review
Verified User
Review Source
Amazon is the big player in the data game right now as it even seems to push Google out of the way in some instances. Because of this you know they treat your data well and also deal with a ton themselves. That makes them good at a comparably smaller data set like most companies have.
Thomas Young | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Review Source
Amazon Elastic MapReduce is useful in cases where two conditions are met. First, that you are planning on using multiple big data tools simultaneously to analyze big data sets. And second, that you need a tool that simplifies managing big data tools. If these two conditions are met, MapReduce does a great job. The user interface is simple. The program eliminates some programming requirements. The software also makes setting up big data analyses much easier. With these benefits acknowledged, MapReduce is not a good tool for "small" data analyses, given that there are other tools that do the job quicker and much more professional output. If you're on the fence, try out MapReduce with competing "small" data tools and see if you really need big data software.
November 17, 2017

EMR review

Score 8 out of 10
Vetted Review
Verified User
Review Source
Well suited if you quickly want to setup a distributed compute platform, such as Spark. But you have to be advanced enough that you really want to separate compute from data storage. For example, for certain applications packaged solution such as MPP databases (e.g. Redshift) is much easier to set up that Spark on EMR and S3 with the appropriate file formats.
October 25, 2017

AWS EMR at a glance!!

Score 7 out of 10
Vetted Review
Verified User
Review Source
EMR is suited if the jobs are long running and doesn't really need much monitoring. EMR is really flexible in processing the data on s3 as a developer doesn't need to spend time on debugging the connections to s3 from a big data framework as most of the configuration is taken care of by Amazon. Very cheap when compared to most of the solutions on the market and the ready to go configuration at the launch time reduces the amount of time required for admin tasks. So, considering the cheap cost, processing options on s3 and scalability via adding task nodes, EMR serves a better purpose for startups considering open source and cost efficient options.

However, EMR comes with its own disadvantages. There is no proper UI to track real time jobs which is however possible with Enterprise editions like Cloudera, Hortonworks etc. EMR could provide an interface to add workbooks and code snippets in the cluster as it would reduce the time to submit the tasks. EMR also lags the potential to automatically replace unhealthy nodes.
Score 6 out of 10
Vetted Review
Verified User
Review Source
If the person using EMR does not need much customization, like debugging or other modifications, or the data is not entirely in another cloud, then Amazon Elastic MapReduce is a better option. Otherwise, there are other open source projects available like Cloudera that are available to be used. Products like Cloudera can also be deployed in any cloud, rather than having to stick with Amazon.