We performed a comparison between AWS Lake Formation and Azure Data Factory based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The solution has many features that are applicable to events such as audits."
"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."
"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."
"We use AWS Lake Formation typically for the data warehouse."
"The initial setup is very quick and easy."
"The solution has a good interface and the integration with GitHub is very useful."
"In terms of my personal experience, it works fine."
"The data mapping and the ability to systematically derive data are nice features. It worked really well for the solution we had. It is visual, and it did the transformation as we wanted."
"The best part of this product is the extraction, transformation, and load."
"The solution is okay."
"The most valuable feature is the ease in which you can create an ETL pipeline."
"The security of the agent that is installed on-premises is very good."
"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."
"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."
"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."
"For the end-users, it's not as user-friendly as it could be."
"The support and the documentation can be improved."
"Data Factory's monitorability could be better."
"You cannot use a custom data delimiter, which means that you have problems receiving data in certain formats."
"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."
"Data Factory could be improved by eliminating the need for a physical data area. We have to extract data using Data Factory, then create a staging database for it with Azure SQL, which is very, very expensive. Another improvement would be lowering the licensing cost."
"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."
"The one element of the solution that we have used and could be improved is the user interface."
"Data Factory could be improved in terms of data transformations by adding more metadata extractions."
AWS Lake Formation is ranked 12th in Cloud Data Warehouse with 5 reviews while Azure Data Factory is ranked 3rd in Cloud Data Warehouse with 81 reviews. AWS Lake Formation is rated 7.6, while Azure Data Factory is rated 8.0. The top reviewer of AWS Lake Formation writes "Strategically aligning data management in a multi-cloud environment with significant reporting challenges". On the other hand, the top reviewer of Azure Data Factory writes "The data factory agent is quite good but pricing needs to be more transparent". AWS Lake Formation is most compared with Snowflake, Amazon Redshift, Microsoft Azure Synapse Analytics, BigQuery and Amazon EMR, whereas Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and Denodo. See our AWS Lake Formation vs. Azure Data Factory report.
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We monitor all Cloud Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.