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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
13th
Average Rating
7.6
Reviews Sentiment
6.9
Number of Reviews
8
Ranking in other categories
No ranking in other categories
Azure Data Factory
Ranking in Cloud Data Warehouse
2nd
Average Rating
8.0
Reviews Sentiment
7.0
Number of Reviews
91
Ranking in other categories
Data Integration (1st)
 

Mindshare comparison

As of June 2025, in the Cloud Data Warehouse category, the mindshare of AWS Lake Formation is 5.5%, up from 5.6% compared to the previous year. The mindshare of Azure Data Factory is 7.8%, down from 10.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse
 

Featured Reviews

Ramesh Raghavan - PeerSpot reviewer
Centralized repository, offers various cataloging mechanisms for quick data retrieval but data governance capabilities could be better
There are a couple of areas for improvement with Lake Formation. One of the main challenges, especially when dealing with rich media content, like in MarTech (Marketing Technology) or ad agencies, is its versatility. Some clients feel that Lake Formation doesn’t meet their needs and they tend to prefer competitor products for those specific use cases. The second area for improvement is in data governance. Specifically, Lake Formation could enhance its capabilities in audit logs, real-time monitoring, and advanced data governance. This includes managing the entire data lineage—where the data originated, how it moves, and where it’s currently stored. The visibility of the data as it evolves is crucial, and that’s where more advanced governance capabilities would be beneficial.
Joy Maitra - PeerSpot reviewer
Facilitates seamless data pipeline creation with good analytics and and thorough monitoring
Azure Data Factory is a low code, no code platform, which is helpful. It provides many prebuilt functionalities that assist in building data pipelines. Also, it facilitates easy transformation with all required functionalities for analytics. Furthermore, it connects to different sources out-of-the-box, making integration much easier. The monitoring is very thorough, though a more readable version would be appreciable.

Quotes from Members

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

Pros

"AWS Lake Formation lets you see all your data and tables on one screen."
"We use AWS Lake Formation typically for the data warehouse."
"I can easily move data from cold storage to regular storage."
"The most important advantage in using AWS Lake Formation is its ability to connect the data lake to the other technologies in AWS. This is what I advise my clients."
"The solution is quite good at handling analytics. It's done a good job at helping us centralize them."
"It is seamlessly integrated within the AWS ecosystem, making it straightforward to manage access patterns for AWS-native services."
"AWS Lake Formation works hand in hand with other products."
"The solution has many features that are applicable to events such as audits."
"Data Factory's best features include its data source connections, GUI for building data pipelines, and target loading within Azure."
"It's cloud-based, allowing multiple users to easily access the solution from the office or remote locations. I like that we can set up the security protocols for IP addresses, like allow lists. It's a pretty user-friendly product as well. The interface and build environment where you create pipelines are easy to use. It's straightforward to manage the digital transformation pipelines we build."
"Azure Data Factory's most valuable features are the packages and the data transformation that it allows us to do, which is more drag and drop, or a visual interface. So, that eases the entire process."
"The interface of Azure Data Factory is very usable with a more interactive visual experience, making it easier for people who are not as experienced in coding to work with."
"The most important feature is that it can help you do the multi-threading concepts."
"On the tool itself, we've never experienced any bugs or glitches. There haven't been crashes. Stability has been good."
"The feature I found most helpful in Azure Data Factory is the pipeline feature, including being able to connect to different sources. Azure Data Factory also has built-in security, which is another valuable feature."
"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."
 

Cons

"Lake Formation could enhance its capabilities in audit logs, real-time monitoring, and advanced data governance."
"In our experience what could be improved are not the support, performance or monitoring, but at a managerial level, the very expensive professional services of AWS. This could be an area of improvement for them. It's too expensive to acquire their support."
"For the end-users, it's not as user-friendly as it could be."
"If I could improve AWS Lake Formation, I would add more integrations with SageMaker."
"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."
"You need to have data experience to use the product."
"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."
"AWS Lake Formation's pricing could be cheaper."
"The solution needs to be more connectable to its own services."
"The thing we missed most was data update, but this is now available as of two weeks ago."
"Azure Data Factory can improve by having support in the drivers for change data capture."
"Azure Data Factory's pricing in terms of utilization could be improved."
"Data Factory's performance during heavy data processing isn't great."
"There is a problem with the integration with third-party solutions, particularly with SAP."
"It would be better if it had machine learning capabilities."
"We have experienced some issues with the integration. This is an area that needs improvement."
 

Pricing and Cost Advice

"AWS Lake Formation is a bit expensive."
"The price you pay is determined by how much you use it."
"Azure products generally offer competitive pricing, suitable for diverse budget considerations."
"For our use case, it is not expensive. We take into the picture everything: resources, learning curve, and maintenance."
"Pricing appears to be reasonable in my opinion."
"I don't see a cost; it appears to be included in general support."
"ADF is cheaper compared to AWS."
"Data Factory is expensive."
"I would rate Data Factory's pricing nine out of ten."
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Top Industries

By visitors reading reviews
Financial Services Firm
21%
Computer Software Company
14%
Manufacturing Company
8%
Government
6%
Financial Services Firm
14%
Computer Software Company
12%
Manufacturing Company
9%
Government
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about AWS Lake Formation?
It is seamlessly integrated within the AWS ecosystem, making it straightforward to manage access patterns for AWS-native services.
What is your experience regarding pricing and costs for AWS Lake Formation?
The pricing is expensive compared to OpenStack, but cheaper than other cloud environments. It's middle-of-the-road for regular storage yet very cost-effective when using Amazon Glacier for data.
What needs improvement with AWS Lake Formation?
If I could improve AWS Lake Formation, I would add more integrations with SageMaker. I would have built-in functions that provide statistics for the data when using the GUI, such as SageMaker Insig...
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: June 2025.
856,873 professionals have used our research since 2012.