Amazon EMR vs IBM Analytics Engine comparison

Amazon Web Services (AWS) and IBM are both solutions in the Hadoop category. Amazon Web Services (AWS) is ranked #3 with an average rating of 8.5, while IBM is ranked #8. Amazon Web Services (AWS) holds a 12.8% mindshare in H, compared to IBM’s 2.8% mindshare. Additionally, 86% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

Amazon EMR

Read 23 Amazon EMR reviews

1,621 Views
567 Comparison Views

86% willing to recommend

IBM Analytics Engine

Read 1 IBM Analytics Engine review

161 Views
161 Comparison Views

100% willing to recommend

Amazon EMR

IBM Analytics Engine

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Executive Summary

We performed a comparison between Amazon EMR and IBM Analytics Engine based on real PeerSpot user reviews.

Find out what your peers are saying about Cloudera, Apache, Amazon Web Services (AWS) and others in Hadoop.

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Buyer's Guide

Hadoop

September 2025

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Review summaries and opinions

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

Categories and Ranking

Amazon EMR

Ranking in Hadoop

3rd

Average Rating

7.8

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (13th)

IBM Analytics Engine

Ranking in Hadoop

8th

Average Rating

8.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of October 2025, in the Hadoop category, the mindshare of Amazon EMR is 12.8%, down from 14.3% compared to the previous year. The mindshare of IBM Analytics Engine is 2.8%, up from 1.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Hadoop Market Share Distribution
Product	Market Share (%)
Amazon EMR	12.8%
IBM Analytics Engine	2.8%
Other	84.4%

Hadoop

Featured Reviews

Prashant Singh

Vice President -Product Management at Paytm

Seamless data integration enhances reporting efficiency and an easy setup

Amazon EMR has multiple connectors that can connect to various data sources. The service charges are based on processing only, depending on the resources used, which can help save money. It is easy to integrate with other services for storage, allowing data to be shifted to cheaper storage based on usage.

Read full review

Saket Pandey

Product Manager at a hospitality company with 51-200 employees

Good solution for small and medium-sized businesses and highly stable

I would advise instead of only going through other reviews; it would be great if you could schedule a talk with the IBM team that would be helping you implement this solution. They would deep dive into the process and protocols you are currently set up in, and then they will provide you an optimal solution and optimal price. So I believe talking with the support team was really amazing. They even helped us in some other parts as well. It is a good solution for small and medium-sized businesses. Overall, I would rate the solution an eight out of ten because of the support team. They were able to resolve issues, which helped us deploy higher-grade solutions correctly and quickly. We were able to ensure that our processes were working correctly, and we saved about 15-16% of a week's time by using this solution. In terms of return on investment, we saved about $7,000 a month.

Read full review

Quotes from Members

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

Pros

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

"The initial setup is pretty straightforward."

"The solution is scalable."

"When we grade big jobs from on-prem to the cloud, we do it in EMR with Spark."

"This is the best tool for hosts and it's really flexible and 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."

"The initial setup is straightforward."

"It allows users to access the data through a web interface."

More Amazon EMR pros

"The best part was that we could make minor changes in the way we were bifurcating the data, even at a very small scale. The accuracy of conversion was also very high."

Cons

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

"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."

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

"The initial setup was time-consuming."

"There is room for improvement in pricing."

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

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

More Amazon EMR cons

"One area for improvement would be the initial setup stage, which took longer than expected."

Pricing and Cost Advice

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

"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."

"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."

"Amazon EMR is not very expensive."

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

"Amazon EMR's price is reasonable."

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

"The price of the solution is expensive."

More Amazon EMR pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

23%

Educational Organization

12%

Computer Software Company

12%

Manufacturing Company

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	6
Midsize Enterprise	5
Large Enterprise	10

No data available

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?

Compared to others, Amazon seems efficient and is considered good for Big Data workloads. Costs are involved based on cluster resources, data volumes, EC2 ( /products/amazon-ec2-reviews ) instances...

See all answers

What needs improvement with Amazon EMR?

There is room for improvement with respect to retries, handling the volume of data on S3 ( /products/amazon-s3-reviews ) buckets, cluster provisioning, scaling, termination, security, and integrati...

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Comparisons

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Cloudera Distribution for Hadoop vs Amazon EMR

Compared 21% of the time

Apache Spark vs Amazon EMR

Compared 10% of the time

Amazon Redshift vs Amazon EMR

Compared 9% of the time

AWS Lake Formation vs Amazon EMR

Compared 6% of the time

More Amazon EMR Competitors

HPE Ezmeral Data Fabric vs IBM Analytics Engine

Compared 100% of the time

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Product Reports

Buyer's Guide

Amazon EMR

September 2025

Download Amazon EMR product report

Buyer's Guide

Hadoop

September 2025

Download IBM Analytics Engine product report

Also Known As

Amazon Elastic MapReduce

No data available

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.

Amazon Web Services (AWS)

IBM Analytics Engine provides an architecture for Hadoop clusters that decouples the compute and storage tiers. Instead of a permanent cluster formed of dual-purpose nodes, the Analytics Engine allows users to store data in an object storage layer such as IBM Cloud Object Storage and spins up clusters of compute notes when needed. Separating compute from storage helps to transform the flexibility, scalability and maintainability of big data analytics platforms.

IBM

Sample Customers

Yelp

Information Not Available

Find out what your peers are saying about Cloudera, Apache, Amazon Web Services (AWS) and others in Hadoop. Updated: September 2025.

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