AWS Lake Formation vs Amazon EMR comparison

Amazon EMR and AWS Lake Formation are both solutions in the Cloud Data Warehouse category. Amazon EMR is ranked #14 with an average rating of 8.0, while AWS Lake Formation is ranked #10 with an average rating of 8.1. Amazon EMR holds a 3.9% mindshare in CDW, compared to AWS Lake Formation’s 3.5% mindshare. Additionally, 83% of Amazon EMR users are willing to recommend the solution, compared to 85% of AWS Lake Formation users who would recommend it.

Amazon EMR

Read 25 Amazon EMR reviews

3,743 Views
1,535 Comparison Views

83% willing to recommend

AWS Lake Formation

Read 21 AWS Lake Formation reviews

2,398 Views
1,918 Comparison Views

85% willing to recommend

Amazon EMR

AWS Lake Formation

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 18, 2024

Amazon EMR and AWS Lake Formation compete in the big data and cloud storage domain. AWS Lake Formation seems to have the upper hand in data governance and security, making it appealing for organizations with such priorities.

Features: Amazon EMR offers rapid data processing, flexibility in choosing processing frameworks like Spark and Hive, and integration with various data sources. AWS Lake Formation focuses on data lake management, providing fine-grained access controls, data security features, and a simplified setup process integrating well with the AWS ecosystem.

Room for Improvement: Amazon EMR could improve its user interface for easier configuration and reduce complexity for new users. Enhanced automated scaling features would benefit users handling fluctuating workloads. Improved documentation could assist users encountering challenges. AWS Lake Formation could enhance integration with more third-party tools, provide more customization options, and expand its set of workflow templates for complex data operations.

Ease of Deployment and Customer Service: Amazon EMR integrates seamlessly into existing AWS infrastructures, offering extensive customization and scaling options, but its complexity can be challenging. AWS Lake Formation simplifies deployment with guided workflows, making it user-friendly for non-experts. Both products offer robust support, though Lake Formation's guided workflows provide an edge in terms of user-friendliness.

Pricing and ROI: Amazon EMR's pay-as-you-go model can be cost-effective for extensive data processing tasks but may incur higher operational costs due to complexity. AWS Lake Formation aims to reduce data governance overhead costs, presenting better ROI for organizations prioritizing cost-efficiency, security, and streamlined operations.

To learn more, read our detailed AWS Lake Formation vs. Amazon EMR Report (Updated: June 2026).

Buyer's Guide

AWS Lake Formation vs. Amazon EMR

June 2026

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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 Cloud Data Warehouse

14th

Average Rating

7.8

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Hadoop (3rd)

AWS Lake Formation

Ranking in Cloud Data Warehouse

10th

Average Rating

8.0

Reviews Sentiment

5.7

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of August 2026, in the Cloud Data Warehouse category, the mindshare of Amazon EMR is 3.9%, up from 3.3% compared to the previous year. The mindshare of AWS Lake Formation is 3.5%, down from 5.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse Mindshare Distribution
Product	Mindshare (%)
AWS Lake Formation	3.5%
Amazon EMR	3.9%
Other	92.6%

Cloud Data Warehouse

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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Ciro Baldim Guerra

Sr Analytics Engineer at Itau Unibanco S.A.

Has improved data governance by enabling clear ownership and structured access across teams

In my company, Itaú, we don't utilize all AWS offerings due to rigorous security measures. We operate approximately six to eight months behind other available services. I'm uncertain if gaps exist because of this limitation, though the system functions effectively for us. AWS Lake Formation offers column-level access control for databases, but we haven't implemented this feature either because it hasn't been approved by our compliance, governance, or security areas. In our current setup, everyone from my business unit uses the same consumer account. When access is requested for a table, everyone using that business unit account receives access. This could present a security concern, though it benefits new team members who automatically receive all necessary access permissions. However, I struggle to identify specific improvements needed in AWS Lake Formation.

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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

"We are using Amazon EMR to clean the data and transform the data in such a way that the end-user can get the insights faster."

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

"We are using applications, such as Splunk, Livy, Hadoop, and Spark. We are using all of these applications in Amazon EMR and they're helping us a lot."

"I rate Amazon EMR as ten out of ten."

"Overall a good cloud infrastructure and takes the burden of managing the distributed hardware and can easily scale up and scale down as per the requirement of the task at hand."

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

"The initial setup is straightforward."

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

More Amazon EMR pros

"The integration of AWS Lake Formation with the IAM for authentication and authorization is very good; I didn't have any problems in the setup and thought it was simple."

"AWS Lake Formation works hand in hand with other products."

"There is no doubt that this place exceeded my expectations with its incredible ambiance, attentive service, and mouthwatering menu."

"We use AWS Lake Formation typically for the data warehouse."

"We use this to reduce latency from minutes to seconds, as we aim for real-time visibility into patient healthcare monitoring."

"In the shortest form, what I appreciated about AWS Lake Formation was that the schema definition and data cataloging were quite good."

"A favorite feature of AWS Lake Formation is that it provides us with visibility into who has access to a particular table or database in Glue."

"AWS Lake Formation has several valuable features that enhance data management, and one particularly beneficial aspect is how it facilitates better collaboration within data teams."

More AWS Lake Formation pros

Cons

"Better monitoring, debugging, and stability are all needed."

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

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

"One of the lacking features is good web support."

"Amazon EMR can improve by adding some features, such as megastore services and HiveServer2. Additionally, the user interface could be better, similar to what Apache service provides, cross-platform services."

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

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

"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

"There are areas that could be improved in AWS Lake Formation, and functionality that could be included in future releases."

"Information about the pricing, cost, and setup cost of the AWS solutions would be beneficial."

"The solution could make improvements around orchestration and doing some automation stuff on AWS front automation. It would be useful if we could use automation to build images and use hardened images which are CIS compliant."

"It falls short when it comes to more granular access control, such as cell-level or row-level entitlements which is a significant drawback for organizations that require precise control over who can access specific rows of data."

"In our current setup, everyone from my business unit uses the same consumer account. When access is requested for a table, everyone using that business unit account receives access. This could present a security concern, though it benefits new team members who automatically receive all necessary access permissions."

"AWS Lake Formation's pricing could be cheaper."

"You need to have data experience to use the product."

"Rather than creating an additional hundred tools, optimizing a tool to have a centralized location to do governance would be beneficial."

More AWS Lake Formation cons

Pricing and Cost Advice

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

"The cost of Amazon EMR is very high."

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

"Amazon EMR's price is reasonable."

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

"The price of the solution is expensive."

"Amazon EMR is not very expensive."

More Amazon EMR pricing and cost advice

"AWS Lake Formation is a bit expensive."

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Manufacturing Company

10%

Construction Company

Healthcare Company

Financial Services Firm

19%

Construction Company

Outsourcing Company

Manufacturing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	6
Midsize Enterprise	5
Large Enterprise	12

By reviewers
Company Size	Count
Small Business	3
Midsize Enterprise	2
Large Enterprise	15

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

What is your experience regarding pricing and costs for AWS Lake Formation?

I don't understand much about the pricing of AWS Lake Formation, but I know how to search for the cost of Glue jobs, and I use the calculator in Amazon. I use a tool to preview the cost based on th...

See all answers

What needs improvement with AWS Lake Formation?

Regarding areas of AWS Lake Formation that could be improved or enhanced, I prefer not to answer, mainly because I do not believe that I would be the most valuable person to ask, as I have not used...

See all answers

What is your primary use case for AWS Lake Formation?

My usual use cases for AWS Lake Formation involved securing and governing the data resources that we configured in AWS, but we did not use the analytics or machine learning capabilities specificall...

See all answers

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Compared 7% of the time

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Compared 6% of the time

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Compared 6% of the time

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Compared 13% of the time

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Compared 10% of the time

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Compared 9% of the time

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Compared 9% of the time

Snowflake Analytics vs AWS Lake Formation

Compared 5% of the time

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Product Reports

Buyer's Guide

Amazon EMR

August 2026

Download Amazon EMR product report

Buyer's Guide

AWS Lake Formation

August 2026

Download AWS Lake Formation product report

Also Known As

Amazon Elastic MapReduce

No data available

Overview

Amazon EMR simplifies big data processing by offering integration with popular tools. It's scalable and cost-efficient, enabling fast processing while managing infrastructure effortlessly. It's designed for users aiming to streamline data workflows and leverage its batch processing capabilities effectively.

Amazon EMR is a managed service that provides robust features for big data processing. It integrates seamlessly with S3, EC2, Hive, and Spark to facilitate sophisticated data transformation tasks and infrastructure management. It allows organizations to run data lakes, Spark, and Hadoop clusters effortlessly, offering flexibility with on-demand execution and extensive scalability. The platform is valued for its strong processing speed and comprehensive security features, making it ideal for complex data engineering projects. It supports both batch processing and real-time workflows, designed to eliminate hardware management while maintaining cost efficiency and stability.

What are the key features of Amazon EMR?

Cluster Management: Offers intuitive control and configuration of clusters
Integration: Seamlessly integrates with S3, EC2, Spark, and more
Scalability: Provides flexible scaling to meet data demands
Batch Processing: Allows efficient handling of large data sets
Cost Efficiency: Minimizes costs with managed service offerings

What benefits and ROI should be considered?

Processing Speed: Fast performance for data processing tasks
Security: Built-in features ensure data protection
Infrastructure Simplification: Eliminates hardware management needs
Flexibility: Adapts to changing data loads with ease
Affordability: Offers economic processing power

Amazon EMR is implemented by industries such as healthcare and tech processing for complex data tasks like building data lakes or financial data processing. It supports AI-driven analytics and data engineering projects, integrating with SageMaker for predictions and maintaining workflows in public health applications, allowing professionals in different fields to manage data pipelines, resource utilization, and job execution efficiently.

Amazon Web Services (AWS)

AWS Lake Formation streamlines data lake organization by integrating seamlessly with AWS services, ensuring robust access control, and facilitating effective data management. Its extensible framework and centralized data handling make it ideal for cloud environments that require scalability.

AWS Lake Formation offers comprehensive data synchronization with AWS, robust security through fine-grained policies, and seamless team collaboration tools. It centralizes data assets, supports analytics with Glue, and enhances data mesh structures. Its IAM integration supports efficient governance, with reliable data storage and retrieval backed by extensive documentation. While highly efficient within AWS ecosystems, Lake Formation faces integration challenges with third-party libraries, and users experience clutter in its interface. Aspects such as automation, policy management, and debugging are areas for improvement. Enhancements in orchestration, cross-account sharing, and integrations with services like SageMaker are user recommendations.

What are the key features of AWS Lake Formation?

Data Synchronization: Integrates with AWS services for seamless data management.
Security Policies: Implements fine-grained access control for secure data handling.
Team Collaboration: Facilitates cooperation through centralized data management.
Analytics Support: Enhances data processing with Glue integration.
Extensibility: IAM integration allows scalable governance.

What benefits or ROI can users expect?

Scalability: Efficiently manages expanding data volumes.
Cost Efficiency: Reduces cloud data management expenses.
Data Security: Ensures compliance with robust policies.
Comprehensive Support: Access to detailed documentation and AWS resources.

Organizations utilize AWS Lake Formation across various industries to build and manage data lakes, ensuring effective data governance and storage solutions. It helps integrate and transform data, control permissions, and support analytics. From e-commerce to healthcare, AWS Lake Formation delivers centralized data repositories for structured and unstructured data, securing information while providing scalable infrastructure and efficient resource management.

Amazon Web Services (AWS)

Sample Customers

Yelp

bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday

Buyer's Guide

AWS Lake Formation vs. Amazon EMR

June 2026

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