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 10.8% 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

1,599 Views
560 Comparison Views

83% willing to recommend

IBM Analytics Engine

Read 1 IBM Analytics Engine review

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

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Hadoop

December 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

7.0

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 January 2026, in the Hadoop category, the mindshare of Amazon EMR is 10.8%, down from 14.2% compared to the previous year. The mindshare of IBM Analytics Engine is 3.1%, up from 1.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Hadoop Market Share Distribution
Product	Market Share (%)
Amazon EMR	10.8%
IBM Analytics Engine	3.1%
Other	86.1%

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.

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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.

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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 scalable."

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

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

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

"The initial setup is straightforward."

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

"Amazon EMR has multiple connectors that can connect to various data sources."

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

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

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

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

"In Qubole, the interface was very good. I could see many details because in Amazon EMR console, very few details are available."

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

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

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

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

"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."

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."

"The cost of Amazon EMR is very high."

"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."

"The price of the solution is expensive."

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

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

"Amazon EMR's price is reasonable."

"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."

More Amazon EMR pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

22%

Educational Organization

13%

Computer Software Company

Healthcare 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?

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...

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What needs improvement with Amazon EMR?

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What advice do you have for others considering Amazon EMR?

I am working on Amazon EMR but not extensively. Basically, our work is data transformation. Our pipelines work on that exclusively. We have Spark applications, and earlier, we used Amazon EMR exten...

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Product Reports

Buyer's Guide

Amazon EMR

January 2026

Download Amazon EMR product report

Buyer's Guide

Hadoop

December 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 Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop. Updated: December 2025.

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