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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 most valuable features of AWS Lake Formation were the access model itself, as it allows implementation of filters, Blueprints, and row-level and column-level security to mask data that shouldn't be accessed by certain entities, enabling granular control without exposing PII data."
"We use AWS Lake Formation typically for the data warehouse."
"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."
"In the shortest form, what I appreciated about AWS Lake Formation was that the schema definition and data cataloging were quite good."
"We have observed measurable benefits in terms of cost savings, time savings, resource savings, and efficiency improvements in our workflows."
"The LF-Tag system with granular permissions was key to the project as a functionality of AWS Lake Formation."
"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."
"Feature-wise, one of the most valuable ones is the data flows introduced recently in the solution."
"It's a good tool, a good product that does what it's supposed to do well, which is ingesting data from a source to your target, to another cloud, to another source."
"It is very modular; it works well, is very flexible, and you can easily bring in outside capabilities and build any features you want."
"From my experience so far, the best feature is the ability to copy data to any environment."
"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."
"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."
"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."
"I like its integration with SQL pools, its ability to work with Databricks, its pipelines, and the serverless architecture are the most effective features."
 

Cons

"Rather than creating an additional hundred tools, optimizing a tool to have a centralized location to do governance would be beneficial."
"AWS Lake Formation's pricing could be cheaper."
"I think AWS Lake Formation could improve by enforcing the least privilege by design, moving from ad hoc grants to role-based access controls."
"I would appreciate online support, which I don't have access to in my corporation at the bank, so that is important."
"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."
"Despite following official documentation, configuration problems persisted, requiring weeks of support from multiple AWS engineers to resolve."
"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."
"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."
"The pricing scheme is very complex and difficult to understand."
"We have experienced some issues with the integration. This is an area that needs improvement."
"It can improve from the perspective of active logging."
"On the UI side, they could make it a little more intuitive in terms of how to add the radius components."
"The thing we missed most was data update, but this is now available as of two weeks ago."
"The speed and performance need to be improved."
"There's no Oracle connector if you want to do transformation using data flow activity, so Azure Data Factory needs more connectors for data flow transformation."
 

Pricing and Cost Advice

"AWS Lake Formation is a bit expensive."
"The price you pay is determined by how much you use it."
"I rate the product price as six on a scale of one to ten, where one is low price and ten is high price."
"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."
"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."
"Azure products generally offer competitive pricing, suitable for diverse budget considerations."
"Understanding the pricing model for Data Factory is quite complex."
"The pricing model is based on usage and is not cheap."
"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."
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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.
893,164 professionals have used our research since 2012.