Amazon EMR vs Apache Hadoop comparison

Amazon Web Services (AWS) and Apache are both solutions in the Cloud Data Warehouse category. Additionally, 85% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 88% of Apache users who would recommend it.

Amazon EMR

Read 21 Amazon EMR reviews

2,042 Views
1,743 Comparison Views

85% willing to recommend

Apache Hadoop

Read 37 Apache Hadoop reviews

2,045 Views
1,721 Comparison Views

88% willing to recommend

Amazon EMR

Apache Hadoop

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Amazon EMR and Apache Hadoop based on real PeerSpot user reviews.

Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Amazon EMR vs. Apache Hadoop Report (Updated: September 2024).

Buyer's Guide

Amazon EMR vs. Apache Hadoop

September 2024

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Helped 801,394 peers since 2012

Categories and Ranking

Amazon EMR

Average Rating

7.8

Number of Reviews

Ranking in other categories

Hadoop (3rd), Cloud Data Warehouse (8th)

Apache Hadoop

Average Rating

7.8

Number of Reviews

Ranking in other categories

Data Warehouse (6th)

Featured Reviews

ChetanGoyal

AWS / Big Data Engineer at Waste Management, Inc.

Aug 1, 2023

Suitable for online deployments with a serverless architecture

EMR Serverless is useful for online deployments that require a serverless architecture. We were previously using a server-based architecture, but we have since switched to serverless The product is very well-designed. It is easy to use, and it is very cost-effective. The solution eliminates…

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Akhilesh Chipre

Senior Assosiate Consultant at Applied Materials

Apr 11, 2024

Handles huge data volumes and create your own workflows and tables but you need to have deeper knowledge

We primarily use Kafka for intensive data streaming. For batch-based processing, we use Hadoop. Additionally, we have our own custom batch catalog that likely helps prepare data for further analysis or use. We have many projects where our main data storage is done in Hadoop only. All projects take data from Hadoop to provide data insights and reports. Hadoop YARN for resource management is a really good aspect. It is is very good for managing large data volumes. It allows us to monitor data processing effectively. We can see how much data there is, the consumption of RAM or ROM, and how resources are allocated. It's good for managing and previewing the scale of data processing.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The solution is pretty simple to set up."

"It has a variety of options and support systems."

"The solution is scalable."

"One of the valuable features about this solution is that it's managed services, so it's pretty stable, and scalable as much as you wish. It has all the necessary distributions. With some additional work, it's also possible to change to a Spark version with the latest version of EMR. It also has Hudi, so we are leveraging Apache Hudi on EMR for change data capture, so then it comes out-of-the-box in EMR."

"Amazon EMR's most valuable features are processing speed and data storage capacity."

"The initial setup is pretty straightforward."

"The solution helps us manage huge volumes of data."

"The security of the managed workflow and the managed services are the best features for us. Since we inherited their security model and it's all managed services, those are the key benefits for our clients."

More Amazon EMR pros

"The performance is pretty good."

"The most important feature is its ability to handle large volumes. Some of our customers have really large volumes, and it is capable of handling their data in terms of the core volume and daily incremental volume. So, its processing power and speed are most valuable."

"Since both Apache Hadoop and Amazon EC2 are elastic in nature, we can scale and expand on demand for a specific PoC, and scale down when it's done."

"It's good for storing historical data and handling analytics on a huge amount of data."

"Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability."

"The tool's stability is good."

"The most valuable feature is the database."

"The most valuable feature is scalability and the possibility to work with major information and open source capability."

More Apache Hadoop pros

Cons

"The solution can become expensive if you are not careful."

"As people are shifting from legacy solutions to other technologies, Amazon EMR needs to add more features that give more flexibility in managing user data."

"The problem for us is it starts very slow."

"There is no need to pay extra for third-party software."

"The most complicated thing is configuring to the cluster and ensure it's running correctly."

"The dashboard management could be better. Right now, it's lacking a bit."

"The legacy versions of the solution are not supported in the new versions."

"The product must add some of the latest technologies to provide more flexibility to the users."

More Amazon EMR cons

"The key shortcoming is its inability to handle queries when there is insufficient memory. This limitation can be bypassed by processing the data in chunks."

"Hadoop's security could be better."

"The solution needs a better tutorial. There are only documents available currently. There's a lot of YouTube videos available. However, in terms of learning, we didn't have great success trying to learn that way. There needs to be better self-paced learning."

"The load optimization capabilities of the product are an area of concern where improvements are required."

"I would like to see more direct integration of visualization applications."

"Real-time data processing is weak. This solution is very difficult to run and implement."

"From the Apache perspective or the open-source community, they need to add more capabilities to make life easier from a configuration and deployment perspective."

"The stability of the solution needs improvement."

More Apache Hadoop cons

Pricing and Cost Advice

"Amazon EMR's price is reasonable."

"The price of the solution is expensive."

"There is a small fee for the EMR system, but major cost components are the underlying infrastructure resources which we actually use."

"I rate the tool's pricing a five out of ten. It can be expensive since it's a managed service, and if you are not careful, you can run into unexpected charges. You can make a mistake that costs you tens of thousands of dollars. That's happened to us twice, so I'm sensitive to it. We're still trying to work on that. Our smallest client probably spends a hundred thousand dollars yearly on licensing, while our largest is well over a million."

"There is no need to pay extra for third-party software."

"You don't need to pay for licensing on a yearly or monthly basis, you only pay for what you use, in terms of underlying instances."

"The product is not cheap, but it is not expensive."

"The cost of Amazon EMR is very high."

More Amazon EMR pricing and cost advice

"There are no licensing costs involved, hence money is saved on the software infrastructure."

"The price of Apache Hadoop could be less expensive."

"It's reasonable, but there's room for improvement in cost-effectiveness."

"We just use the free version."

"Do take into consider that data storage and compute capacity scale differently and hence purchasing a "boxed" / 'all-in-one" solution (software and hardware) might not be the best idea."

"The price could be better. Hortonworks no longer exists, and Cloudera killed the free version of Hadoop."

"We don't directly pay for it. Our clients pay for it, and they usually don't complain about the price. So, it is probably acceptable."

"If my company can use the cloud version of Apache Hadoop, particularly the cloud storage feature, it would be easier and would cost less because an on-premises deployment has a higher cost during storage, for example, though I don't know exactly how much Apache Hadoop costs."

More Apache Hadoop pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

25%

Computer Software Company

13%

Manufacturing Company

Educational Organization

Financial Services Firm

30%

Computer Software Company

11%

University

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about Amazon EMR?

Amazon EMR is a good solution that can be used to manage big data.

See all answers

What is your experience regarding pricing and costs for Amazon EMR?

I rate the tool's pricing a five out of ten. It can be expensive since it's a managed service, and if you are not careful, you can run into unexpected charges. You can make a mistake that costs you...

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What needs improvement with Amazon EMR?

The solution can become expensive if you are not careful.

See all answers

What do you like most about Apache Hadoop?

It's primarily open source. You can handle huge data volumes and create your own views, workflows, and tables. I can also use it for real-time data streaming.

See all answers

What is your experience regarding pricing and costs for Apache Hadoop?

I would rate the product's subscription-based pricing a six out of ten. It's reasonable, but there's room for improvement in cost-effectiveness.

See all answers

What needs improvement with Apache Hadoop?

The product's availability of comprehensive training materials could be improved for faster onboarding and skill development among team members.

See all answers

Comparisons

Snowflake vs Amazon EMR

Compared 35% of the time

Cloudera Distribution for Hadoop vs Amazon EMR

Compared 28% of the time

Azure Data Factory vs Amazon EMR

Compared 10% of the time

Amazon Redshift vs Amazon EMR

Compared 9% of the time

Microsoft Azure Synapse Analytics vs Amazon EMR

Compared 4% of the time

More Amazon EMR Competitors

Azure Data Factory vs Apache Hadoop

Compared 18% of the time

Oracle Exadata vs Apache Hadoop

Compared 15% of the time

Microsoft Azure Synapse Analytics vs Apache Hadoop

Compared 13% of the time

BigQuery vs Apache Hadoop

Compared 9% of the time

Teradata vs Apache Hadoop

Compared 9% of the time

More Apache Hadoop Competitors

Product Reports

Buyer's Guide

Amazon EMR

September 2024

Download Amazon EMR product report

Buyer's Guide

Apache Hadoop

September 2024

Download Apache Hadoop product report

Also Known As

Amazon Elastic MapReduce

No data available

Learn More

Amazon Web Services (AWS)

Apache

Overview

Amazon Elastic MapReduce (Amazon EMR) is a web service that makes it easy to quickly and cost-effectively process vast amounts of data. Amazon EMR simplifies big data processing, providing a managed Hadoop framework that makes it easy, fast, and cost-effective for you to distribute and process vast amounts of your data across dynamically scalable Amazon EC2 instances.

The Apache Hadoop project develops open-source software for reliable, scalable, distributed computing. The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.

Sample Customers

Yelp

Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web Lab

Buyer's Guide

Amazon EMR vs. Apache Hadoop

September 2024

Free Report: Amazon EMR vs. Apache Hadoop

Find out what your peers are saying about Amazon EMR vs. Apache Hadoop and other solutions. Updated: September 2024.

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