AWS Lake Formation vs Azure Data Factory comparison

"We use AWS Lake Formation typically for the data warehouse."

"The solution has many features that are applicable to events such as audits."

"AWS Lake Formation lets you see all your data and tables on one screen."

"I can easily move data from cold storage to regular storage."

"AWS Lake Formation works hand in hand with other products."

"The solution is quite good at handling analytics. It's done a good job at helping us centralize them."

"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."

"It is seamlessly integrated within the AWS ecosystem, making it straightforward to manage access patterns for AWS-native services."

"The platform excels in data transformation with its user-friendly interface and robust monitoring capabilities, making ETL processes seamless."

"We have found the bulk load feature very valuable."

"The initial setup is very quick and easy."

"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."

"Azure Data Factory became more user-friendly when data-flows were introduced."

"The most valuable aspect is the copy capability."

"I can do everything I want with SSIS and Azure Data Factory."

"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."

"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."

"For the end-users, it's not as user-friendly as it could be."

"AWS Lake Formation's pricing could be cheaper."

"If I could improve AWS Lake Formation, I would add more integrations with SageMaker."

"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."

"You need to have data experience to use the product."

"Lake Formation could enhance its capabilities in audit logs, real-time monitoring, and advanced data governance."

"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."

"The product could provide more ways to import and export data."

"When the record fails, it's tough to identify and log."

"The initial setup is not very straightforward."

"There is always room to improve. There should be good examples of use that, of course, customers aren't always willing to share. It is Catch-22. It would help the user base if everybody had really good examples of deployments that worked, but when you ask people to put out their good deployments, which also includes me, you usually got, "No, I'm not going to do that." 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."

"Azure Data Factory could benefit from improvements in its monitoring capabilities to provide a more robust feature set. Enhancing the ease of deployment to higher environments within Azure DevOps would be beneficial, as the current process often requires extensive scripting and pipeline development. It is also known for the flexibility of the data flow feature, particularly in supporting more dynamic data-driven architectures. These enhancements would contribute to a more seamless and efficient workflow within GitLab."

"The tool’s workflow is not user-friendly. It should also improve its orchestration monitoring."

"Data Factory would be improved if it were a little more configuration-oriented and not so code-oriented and if it had more automated features."

"The speed and performance need to be improved."

"AWS Lake Formation is a bit expensive."

"The price you pay is determined by how much you use it."

"Azure Data Factory gives better value for the price than other solutions such as Informatica."

"Product is priced at the market standard."

"I would rate Data Factory's pricing nine out of ten."

"Azure products generally offer competitive pricing, suitable for diverse budget considerations."

"The price is fair."

"I would not say that this product is overly expensive."

"The solution's pricing is competitive."