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 7.8, while IBM is ranked #8. Amazon Web Services (AWS) holds a 10.4% mindshare in H, compared to IBM’s 3.1% mindshare. Additionally, 83% 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 25 Amazon EMR reviews

1,742 Views
592 Comparison Views

83% willing to recommend

IBM Analytics Engine

Read 1 IBM Analytics Engine review

212 Views
201 Comparison Views

100% willing to recommend

Amazon EMR

IBM Analytics Engine

Comparison Buyer's Guide

Download the report

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 Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop.

To learn more, read our detailed Hadoop Report (Updated: February 2026).

Buyer's Guide

Hadoop

February 2026

Download the complete report

Helped 882,961 peers since 2012

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

7.0

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 February 2026, in the Hadoop category, the mindshare of Amazon EMR is 10.4%, down from 14.0% compared to the previous year. The mindshare of IBM Analytics Engine is 3.1%, up from 1.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Hadoop Market Share Distribution
Product	Market Share (%)
Amazon EMR	10.4%
IBM Analytics Engine	3.1%
Other	86.5%

Hadoop

Featured Reviews

reviewer1343079

Senior Chief Engineer (Enterprise System Presales/Postsales) at a tech vendor with 10,001+ employees

Has simplified ETL workflows with on-demand processing but needs improved cost efficiency and visibility

I have used AWS Glue with S3 for making tables and databases, but regarding Amazon EMR, I do not remember much as we are currently using it very minimally. This is my observation: In EKS, we have had to deploy by ourselves because EKS does not provide the Hadoop framework, Spark, Hive, and everything, but we have completed all the deployment ourselves. Whereas Amazon EMR provides all these things. The cost factor differs significantly. When you run Spark application on EKS, you run at the pod level, so you can control the compute cost. But in Amazon EMR, when you have to run one application, you have to launch the entire EC2. In Qubole, the interface was very good. I could see many details because in Amazon EMR console, very few details are available. In Qubole, at one link, you can get all the details of what is happening, how the processes are running, and the cost decreased by using Qubole. I found Qubole more user-friendly and cost-effective. From the security point of view, we had to open some access rights to Qubole, which might be a drawback in comparison to Amazon EMR which is native to AWS.

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

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

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

"The ability to resize the cluster is what really makes it stand out over other Hadoop and big data solutions."

"In Amazon EMR it is easy to rebuild anything, easy to upgrade and has good fault tolerance."

"Amazon EMR provides out-of-the-box functionality because we can deploy and get Spark functionality over Hadoop."

"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."

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

"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."

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

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

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

"The initial setup was time-consuming."

"The product's features for storing data in static clusters could be better."

"Amazon EMR is continuously improving, but maybe something like CI/CD out-of-the-box or integration with Prometheus Grafana."

"Spark jobs take longer on Amazon EMR compared to previous experiences."

"I feel some lack of functionality in Amazon EMR."

"Modules and strategies should be better handled and notified early in advance."

More Amazon EMR cons

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

Pricing and Cost Advice

"The price of the solution is 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."

"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."

"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 cost of Amazon EMR is very high."

"Amazon EMR is not very expensive."

More Amazon EMR pricing and cost advice

Information not available

See which vendors are best for you

Use our free recommendation engine to learn which Hadoop solutions are best for your needs.

See recommendations

882,961 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

20%

Healthcare Company

Computer Software Company

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	12

No data available

Questions from the Community

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

I would rate the price for Amazon EMR, where one is high and ten is low, as a good one.

See all answers

What needs improvement with Amazon EMR?

I feel some lack of functionality in Amazon EMR. I have thoughts on what would be great to see in the product, such as AI/ML features or additional options.

See all answers

What advice do you have for others considering Amazon EMR?

I find it easy to integrate Amazon EMR with other AWS services like S3 or EC2 for data processing needs. I would rate this review as eight out of ten.

See all answers

Ask a question

Earn 20 points

Comparisons

Snowflake vs Amazon EMR

Compared 14% of the time

Cloudera Distribution for Hadoop vs Amazon EMR

Compared 9% of the time

Apache Spark vs Amazon EMR

Compared 7% of the time

Amazon Redshift vs Amazon EMR

Compared 6% of the time

More Amazon EMR Competitors

HPE Data Fabric vs IBM Analytics Engine

Compared 44% of the time

Spark SQL vs IBM Analytics Engine

Compared 23% of the time

More IBM Analytics Engine Competitors

Product Reports

Buyer's Guide

Amazon EMR

February 2026

Download Amazon EMR product report

Buyer's Guide

Hadoop

February 2026

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 Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop. Updated: February 2026.

DOWNLOAD NOW

882,961 professionals have used our research since 2012.

See our list of best Hadoop vendors.

We monitor all Hadoop reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.