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AWS Lake Formation vs Azure Data Factory comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 18, 2024

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

AWS Lake Formation
Ranking in Cloud Data Warehouse
9th
Average Rating
8.0
Reviews Sentiment
5.7
Number of Reviews
21
Ranking in other categories
No ranking in other categories
Azure Data Factory
Ranking in Cloud Data Warehouse
5th
Average Rating
8.0
Reviews Sentiment
6.8
Number of Reviews
94
Ranking in other categories
Data Integration (4th)
 

Mindshare comparison

As of May 2026, in the Cloud Data Warehouse category, the mindshare of AWS Lake Formation is 4.1%, down from 5.3% compared to the previous year. The mindshare of Azure Data Factory is 5.3%, down from 7.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Mindshare Distribution
ProductMindshare (%)
Azure Data Factory5.3%
AWS Lake Formation4.1%
Other90.6%
Cloud Data Warehouse
 

Featured Reviews

Ciro Baldim Guerra - PeerSpot reviewer
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.
KandaswamyMuthukrishnan - PeerSpot reviewer
Director at a computer software company with 1,001-5,000 employees
Integrates diverse data sources and streamlines ETL processes effectively
Regarding potential areas of improvement for Azure Data Factory, there is a need for better data transformation, especially since many people are now depending on DataBricks more for connectivity and data integration. Azure Data Factory should consider how to enhance integration or filtering for more transformations, such as integrating with Spark clusters. I am satisfied with Azure Data Factory so far, but I suggest integrating some AI functionality to analyze data during the transition itself, providing insights such as null records, common records, and duplicates without running a separate pipeline or job. The monitoring tools in Azure Data Factory are helpful for optimizing data pipelines; while the current feature is adequate, they can improve by creating a live dashboard to see the online process, including how much percentage has been completed, which will be very helpful for people who are monitoring the pipeline.

Quotes from Members

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

Pros

"The features and capabilities of AWS Lake Formation that I have found most valuable are that it is really convenient to see all the different data assets that were configured and understand who has and what type of service has or does not have access to those services."
"Every solution has its pros and cons, however, for our purposes, this solution works quite well for us."
"The main benefits that I have seen from using AWS Lake Formation are related to FinOps because you have control of your data and can track your costs since AWS Lake Formation is integrated into a unique platform, which is AWS Cloud Service."
"AWS Lake Formation works hand in hand with other products."
"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."
"We use this to reduce latency from minutes to seconds, as we aim for real-time visibility into patient healthcare monitoring."
"I can easily move data from cold storage to regular storage."
"AWS Lake Formation significantly improves the structure of the data mesh, making it superior to previous structures we used."
"It is very modular. It works well. We've used Data Factory and then made calls to libraries outside of Data Factory to do things that it wasn't optimized to do, and it worked really well. It is obviously proprietary in regards to Microsoft created it, but it is pretty easy and direct to bring in outside capabilities into Data Factory."
"The most valuable feature of this solution is that it allows more data between on-premises and cloud solutions."
"When it comes to our business requirements, this solution has worked well for us."
"The most valuable feature of Azure Data Factory is the core features that help you through the whole Azure pipeline or value chain."
"The solution has a good interface and the integration with GitHub is very useful."
"I find the most valuable feature in Azure Data Factory to be its ability to handle large datasets."
"The tools are impressively well-integrated, allowing quick development of ETL, big data, data warehousing and machine learning solutions with the flexibility to grow and adapt to changing or enhanced requirements."
"My only advice is that Azure Data Factory, particularly for data ingestion, is a good choice."
 

Cons

"The main challenge we faced with AWS Lake Formation was related to cross-account sharing. Granting access to other AWS accounts for tables or databases in a different AWS account was somewhat difficult."
"For the end-users, it's not as user-friendly as it could be."
"The solution could make improvements around orchestration and doing some automation stuff on AWS front automation."
"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."
"Despite following official documentation, configuration problems persisted, requiring weeks of support from multiple AWS engineers to resolve."
"I haven't seen any measurable benefits from using AWS Lake Formation, such as time saving, resource saving, or efficiency improvements."
"For the end-users, it's not as user-friendly as it could be."
"Rather than creating an additional hundred tools, optimizing a tool to have a centralized location to do governance would be beneficial."
"It's essentially just a black box. There is some monitoring that can be done, but when something goes wrong, even simple fixes are difficult to troubleshoot."
"The speed and performance need to be improved."
"Azure Data Factory can improve by having support in the drivers for change data capture."
"Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically."
"There are performance issues, particularly with the underlying compute, which should be configurable."
"When working with AWS, we have noticed that the difference between ADF and AWS is that AWS is more customer-focused. They're more responsive compared to any other company. ADF is not as good as AWS, but it should be. If AWS is ten out of ten, ADF is around eight out of ten. I think AWS is easier to understand from the GUI perspective compared to ADF."
"When we initiated the cluster, it took some time to start the process."
"The Microsoft documentation is too complicated."
 

Pricing and Cost Advice

"AWS Lake Formation is a bit expensive."
"The pricing is a bit on the higher end."
"The solution's fees are based on a pay-per-minute use plus the amount of data required to process."
"The licensing model for Azure Data Factory is good because you won't have to overpay. Pricing-wise, the solution is a five out of ten. It was not expensive, and it was not cheap."
"It seems very low initially, but as the data grows, the solution’s bills grow exponentially."
"I am aware of the pricing of Azure Data Factory, but I prefer not to disclose specific details."
"My company is on a monthly subscription for Azure Data Factory, but it's more of a pay-as-you-go model where your monthly invoice depends on how many resources you use. On a scale of one to five, pricing for Azure Data Factory is a four. It's just the usage fees my company pays monthly."
"The price is fair."
"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."
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Top Industries

By visitors reading reviews
Financial Services Firm
22%
Manufacturing Company
9%
Retailer
6%
Government
6%
Financial Services Firm
12%
Computer Software Company
10%
Manufacturing Company
9%
Government
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise2
Large Enterprise15
By reviewers
Company SizeCount
Small Business31
Midsize Enterprise20
Large Enterprise57
 

Questions from the Community

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...
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...
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...
How do you select the right cloud ETL tool?
AWS Glue and Azure Data factory for ELT best performance cloud services.
How does Azure Data Factory compare with Informatica PowerCenter?
Azure Data Factory is flexible, modular, and works well. In terms of cost, it is not too pricey. It offers the stability and reliability I am looking for, good scalability, and is easy to set up an...
How does Azure Data Factory compare with Informatica Cloud Data Integration?
Azure Data Factory is a solid product offering many transformation functions; It has pre-load and post-load transformations, allowing users to apply transformations either in code by using Power Q...
 

Overview

 

Sample Customers

bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday
1. Adobe 2. BMW 3. Coca-Cola 4. General Electric 5. Johnson & Johnson 6. LinkedIn 7. Mastercard 8. Nestle 9. Pfizer 10. Samsung 11. Siemens 12. Toyota 13. Unilever 14. Verizon 15. Walmart 16. Accenture 17. American Express 18. AT&T 19. Bank of America 20. Cisco 21. Deloitte 22. ExxonMobil 23. Ford 24. General Motors 25. IBM 26. JPMorgan Chase 27. Microsoft (Azure Data Factory is developed by Microsoft) 28. Oracle 29. Procter & Gamble 30. Salesforce 31. Shell 32. Visa
Find out what your peers are saying about AWS Lake Formation vs. Azure Data Factory and other solutions. Updated: April 2026.
893,244 professionals have used our research since 2012.