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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
8th
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
6.7
Number of Reviews
96
Ranking in other categories
Data Integration (4th)
 

Mindshare comparison

As of June 2026, in the Cloud Data Warehouse category, the mindshare of AWS Lake Formation is 3.8%, down from 5.4% compared to the previous year. The mindshare of Azure Data Factory is 5.3%, down from 7.6% 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 Formation3.8%
Other90.9%
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

"There is no doubt that this place exceeded my expectations with its incredible ambiance, attentive service, and mouthwatering menu."
"We have observed measurable benefits in terms of cost savings, time savings, resource savings, and efficiency improvements in our workflows."
"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 significantly improves the structure of the data mesh, making it superior to previous structures we used."
"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."
"AWS Lake Formation works hand in hand with other products."
"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 lets you see all your data and tables on one screen."
"One advantage of Azure Data Factory is that it's fast, unlike SSIS and other on-premise tools. It's also very convenient because it has multiple connectors. The availability of native connectors allows you to connect to several resources to analyze data streams."
"The tool's most valuable features are its connectors. It has many out-of-the-box connectors. We use ADF for ETL processes. Our main use case involves integrating data from various databases, processing it, and loading it into the target database. ADF plays a crucial role in orchestrating these ETL workflows."
"The data flows were beneficial, allowing us to perform multiple transformations."
"The valuable feature of Azure Data Factory is its integration capability, as it goes well with other components of Microsoft Azure."
"The most valuable features of the solution are its ease of use and the readily available adapters for connecting with various sources."
"My only advice is that Azure Data Factory, particularly for data ingestion, is a good choice."
"The function of the solution is great."
"We have found the bulk load feature very valuable."
 

Cons

"Athena can be a bit clunky when writing queries, indicating a potential enhancement point for easier user interaction with query tools such as DataGrip using provided driver JARs."
"AWS Lake Formation's pricing could be cheaper."
"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."
"I think AWS Lake Formation could improve by enforcing the least privilege by design, moving from ad hoc grants to role-based access controls."
"Rather than creating an additional hundred tools, optimizing a tool to have a centralized location to do governance would be beneficial."
"The initial onboarding process is challenging because creating a plan takes a month to a month and a half to build out."
"For the end-users, it's not as user-friendly as it could be."
"Information about the pricing, cost, and setup cost of the AWS solutions would be beneficial."
"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."
"There is room for improvement primarily in its streaming capabilities. For structured streaming and machine learning model implementation within an ETL process, it lags behind tools like Informatica."
"For some of the data, there were some issues with data mapping. Some of the error messages were a little bit foggy. There could be more of a quick start guide or some inline examples. The documentation could be better."
"My only problem is the seamless connectivity with various other databases, for example, SAP."
"The tool’s workflow is not user-friendly. It should also improve its orchestration monitoring."
"Azure Data Factory uses many resources and has issues with parallel workflows."
"Data Factory's performance during heavy data processing isn't great."
"I have not found any real shortcomings within the product."
 

Pricing and Cost Advice

"AWS Lake Formation is a bit expensive."
"This is a cost-effective solution."
"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."
"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 licensing cost is included in the Synapse."
"Understanding the pricing model for Data Factory is quite complex."
"Our licensing fees are approximately 15,000 ($150 USD) per month."
"The pricing is pay-as-you-go or reserve instance. Of the two options, reserve instance is much cheaper."
"The solution's pricing is competitive."
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Top Industries

By visitors reading reviews
Financial Services Firm
21%
Manufacturing Company
8%
Government
6%
Computer Software Company
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.
896,942 professionals have used our research since 2012.