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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
95
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

"We use this to reduce latency from minutes to seconds, as we aim for real-time visibility into patient healthcare monitoring."
"The most important advantage of using AWS Lake Formation is its ability to connect the data lake to the other technologies in AWS."
"The LF-Tag system with granular permissions was key to the project as a functionality of AWS Lake Formation."
"AWS Lake Formation significantly improves the structure of the data mesh, making it superior to previous structures we used."
"The solution is quite good at handling analytics."
"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."
"We use AWS Lake Formation typically for the data warehouse."
"The solution is quite good at handling analytics. It's done a good job at helping us centralize them."
"What I like best about Azure Data Factory is that it allows you to create pipelines, specifically ETL pipelines. I also like that Azure Data Factory has connectors and solves most of my company's problems."
"When it comes to our business requirements, this solution has worked well for us."
"Data Factory itself is great. It's pretty straightforward. You can easily add sources, join and lookup information, etc. The ease of use is pretty good."
"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 data pipeline and the orchestration functionality are the most valuable aspects of the solution, and the interface is very good, as it seeks to be very responsive and intuitive."
"Synapse was the better choice for us to implement, as it has a lot of out-of-the-box connectors that we can utilize for data transformation and organization."
"The reason that we implemented this product is for the full integration with the whole Azure environment."
"It is easy to integrate."
 

Cons

"For the end-users, it's not as user-friendly as it could be."
"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."
"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."
"I haven't seen any measurable benefits from using AWS Lake Formation, such as time saving, resource saving, or efficiency improvements."
"Lake Formation could enhance its capabilities in audit logs, real-time monitoring, and advanced data governance."
"Information about the pricing, cost, and setup cost of the AWS solutions would be beneficial."
"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."
"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."
"There's space for improvement in the development process of the data pipelines."
"They don't have enough good examples. Microsoft probably just needs to pay one of their partners to build 20 or 30 examples of functional Data Factories and then share them as a user base."
"To my mind, the solution needs to be more connectable to its own services."
"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."
"They should work on optimizing their licensing model and pricing structure."
"User-friendliness and user effectiveness are unquestionably important, and it may be a good option here to improve the user experience. However, I believe that more and more sophisticated monitoring would be beneficial."
"Lacks a decent UI that would give us a view of the kinds of requests that come in."
"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."
 

Pricing and Cost Advice

"AWS Lake Formation is a bit expensive."
"ADF is cheaper compared to AWS."
"While I can't specify the actual cost, I believe it is reasonably priced and comparable to similar products."
"Pricing appears to be reasonable in my opinion."
"The licensing cost is included in the Synapse."
"This is a cost-effective solution."
"Azure products generally offer competitive pricing, suitable for diverse budget considerations."
"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."
"The pricing model is based on usage and is not cheap."
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Top Industries

By visitors reading reviews
Financial Services Firm
22%
Manufacturing Company
8%
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 Enterprise21
Large Enterprise63
 

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.
894,998 professionals have used our research since 2012.