Amazon EMR is ideal for Hadoop-based processing
The AWS stack is a big component of the majority of our work. When necessary, EMR is employed in a number of these settings. When we need …
Overview
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…
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What is Amazon EMR?
Amazon EMR Technical Details
| Operating Systems | Unspecified |
|---|---|
| Mobile Application | No |
Frequently Asked Questions
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.
Reviewers rate Support Rating highest, with a score of 9.
The most common users of Amazon EMR are from Enterprises (1,001+ employees).
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(60)Attribute Ratings
Reviews
(1-19 of 19)Companies can't remove reviews or game the system. Here's why
April 22, 2022
Amazon EMR is ideal for Hadoop-based processing
- Faster than prior on-premise systems to put in place.
- Open source software is supported.
- Reduces the cost of production.
- Automation of processing jobs creation and deletion.
- The cost of this service is more expensive than similar ones.
- Getting everything up and running at the beginning is a lengthy process.
April 19, 2022
Amazon EMR - fast, and elastic
- They have excellent tech support
- Reduced processing times
- Easy to configure
- Pricing should be better
- User Interface should be more attractive
- Faster ramp up
April 11, 2022
Amazon EMR is worth it when you have experience
- very easy to configure
- easy to manage large amounts of data
- very quick in executing transformations
- not a recommended service to mange smaller amounts of data
- expensive
- not the best user interface out there
April 09, 2022
EMR: Great Services for Analytics
- Big data processing.
- The resizing feature is good.
- Ease of use and creating new clusters.
- The user interface could use a facelift.
- Overhead delay in starting clusters.
- Big learning curve for someone who hasn't used a program like this before.
April 08, 2022
Good product to try with...Amazon EMR.
- Manage large database well.
- Usage Monitoring.
- Quick
- Cost effective.
- Little bit complex with setting it up.
- Could be costly of not configured well.
- Typical to manage.
April 08, 2022
Amazon EMR - It's very intuitive and easy to use.
- Faster processing.
- The distributed computation of the calculations.
- Easy to setup.
- Monitoring as an add up.
- Can be integrated with lots of technologies.
- Overhead delay in starting clusters which can cause problems.
April 06, 2022
My chosen scaleable cloud platform
- Scalability
- Costings
- Flexibility
- Costs
- Auto-scale
April 06, 2022
AWS has it all!
- Scalable
- Flexible
- Good documentation
- Cost effective
- Integration with ERP for SMEs.
- To connect to non cloud solutions and replicate data for backup.
- Better performance metrics for business people such as cost benefits.
April 06, 2022
Awesome Services to process data seamlessly
- Process large data seamlessly.
- Easy to integrate with other services.
- Very time and cost effective.
- Hard to manage.
- It can suggest cost saving tricks because it can be costly if not done right.
- should be able replicate previous steps.
December 10, 2021
Amazon EMR is the extremely large datasets transformation solution
- Quick.
- Massive.
- Relatively cheap.
- Harder to manager than ec2.
- Could be very costly if not doing right.
- RAM is fixed.
December 03, 2021
Amazon EMR - Truly elastic
- Big data ETL
- Data ingestion
- Ad hoc query support
- Library management
- Storing historical steps
- Downloading EMR job logs could be easier
September 22, 2020
Amazon EMR Review
- Provides the Amazon EMR highlights, product details, and pricing information.
- Simplifies running big data frameworks.
- Analyzes vast amounts of data.
- Freezes sometimes.
- Glitches a lot.
- Runs slow.
September 20, 2020
AWS's EMR: the best option out there
- Easier to implement than older on-premise solutions
- Works with open source technologies.
- Keeps processing cost low.
- It is flexible and works also for short term workloads and the pricing changes to that model.
- You definitely need to be trained before using it because the interface can be a little confusing. It is a professional service model, so I recommend a certified dev.
September 11, 2020
Amazon EMR is a great way to manage and analyze data!
- Makes massive data easier to manage
- Backed by Amazon and AWS
- Makings analyzing data easy
- Support more data frameworks
- API integration
- Cloud service integration
February 04, 2019
Amazon Elastic MapReduce is Worth the Effort if You Really Need Big Data Management, Just Make Sure You Really Need It
- Amazon Elastic MapReduce works well for managing analyses that use multiple tools, such as Hadoop and Spark. If it were not for the fact that we use multiple tools, there would be less need for MapReduce.
- MapReduce is always on. I've never had a problem getting data analyses to run on the system. It's simple to set up data mining projects.
- Amazon Elastic MapReduce has no problems dealing with very large data sets. It processes them just fine. With that said, the outputs don't come instantaneously. It takes time.
- The analytical processes generally run quicker with the standalone tools of Hadoop, Spark, and others. If you only use one big data tool and don't really need things simplified, then Elastic MapReduce is more of an overhead tool that doesn't add much value.
- The analytical capabilities of Elastic MapReduce are nowhere near as complex or broad as non-big data tools. I would suggest not using the tool unless your data really is big data.
- The machine learning capabilities of Elastic MapReduce (using the big data tools of Hadoop/Spark) are good but are not as easy to use as other machine learning tools.
January 18, 2018
Amazon EMR- Great cloud based Hadoop platform
- Distributed computing
- Fault tolerant
- Uptime
- Providing user friendly tools for hdfs access
- More simpler apis for easy access and processsing
- Memory requirenent
November 17, 2017
EMR review
- Ease of use and ease to setup
- Autoscaling functionality
- Integrated into the AWS environment
- Cost overhead is a bit high
- Limited versions of frameworks that can be used
October 25, 2017
AWS EMR at a glance!!
- EMR does well in managing the cost as it uses the task node cores to process the data and these instances are cheaper when the data is stored on s3. It is really cost efficient. No need to maintain any libraries to connect to AWS resources.
- EMR is highly available, secure and easy to launch. No much hassle in launching the cluster (Simple and easy).
- EMR manages the big data frameworks which the developer need not worry (no need to maintain the memory and framework settings) about the framework settings. It's all setup on launch time. The bootstrapping feature is great.
- Sometimes bootstrapping certain tools comes with debugging costs. The tools provided by some of the enterprise editions are great compared to EMR.
- Like some of the enterprise editions EMR does not provide on premises options.
- No UI client for saving the workbooks or code snippets. Everything has to go through submitting process. Not really convenient for tracking the job as well.
June 22, 2016
Research Experience with Amazon EMR
- The cluster size of MapReduce is very dynamic and therefore scalability is good for EMR.
- It also works well with other Amazon Web Services like Amazon Simple Storage Service, which means that data can be taken from those services and written back to them.
- I tried using the in-house hosting at the university I work in, but there would be a lot of complications with technical support required. For Amazon, the support and documentation was good to solve these problems faster.
- It would have been better if packages like HBase and Flume were available with Amazon EMR. This would make the product even more helpful in some cases.
- Products like Cloudera provide the options to move the whole deployment into a dedicated server and use it at our discretion. This would have been a good option if available with EMR.
- If EMR gave the option to be used with any choice of cloud provider, it would have helped instead of having to move the data from another cloud service to S3.