We performed a comparison between AWS Lake Formation and Microsoft Parallel Data Warehouse 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."
"Collecting the data through SSIS packages from different sources and putting them all in one data repository is the most powerful thing. While others have this feature, they don't have the simplicity or ease of use when getting a resource and knowing everything about it."
"We are able to monitor daily jobs, so if there is anything that needs to be done then we can do it."
"It is a stable solution...It is a scalable solution."
"One of the most important features is the ease of using MS SQL."
"The most valuable feature for me is querying."
"Microsoft Parallel Data Warehouse provides good firewall processing in terms of response time."
"It performs very well overall."
"Data collection and reporting are valuable features of the solution."
"AWS Lake Formation's pricing could be cheaper."
"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."
"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."
"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."
"I would like to see better visualization features."
"The query is slow if we don't optimize it."
"The only issue with the product is that the process is very slow when we have a huge amount of data."
"More tools to help designers should be included."
"I think that the error messages need to be made more specific."
"The solution is expensive and has room for improvement."
"It needs more compatibility with common BI tools."
"Sometimes, the product requires rolling back to its previous version during a software update. This particular area could be enhanced."
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AWS Lake Formation is ranked 12th in Cloud Data Warehouse with 5 reviews while Microsoft Parallel Data Warehouse is ranked 8th in Data Warehouse with 32 reviews. AWS Lake Formation is rated 7.6, while Microsoft Parallel Data Warehouse is rated 7.6. 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 Microsoft Parallel Data Warehouse writes "An easy to setup tool that allows its users to write stored procedure, making it a scalable product". AWS Lake Formation is most compared with Snowflake, Azure Data Factory, Amazon Redshift, Microsoft Azure Synapse Analytics and BigQuery, whereas Microsoft Parallel Data Warehouse is most compared with Microsoft Azure Synapse Analytics, Oracle Exadata, SAP BW4HANA, VMware Tanzu Greenplum and Snowflake. See our AWS Lake Formation vs. Microsoft Parallel Data Warehouse 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.
