We performed a comparison between Azure Data Factory 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."We haven't had any issues connecting it to other products."
"It's extremely consistent."
"The data factory agent is quite good and programming or defining the value of jobs, processes, and activities is easy."
"Allows more data between on-premises and cloud solutions"
"The most valuable features are data transformations."
"Feature-wise, one of the most valuable ones is the data flows introduced recently in the solution."
"The most valuable features of Azure Data Factory are the flexibility, ability to move data at scale, and the integrations with different Azure components."
"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 most valuable feature of this solution is performance."
"The most valuable feature for me is querying."
"Tools like the BI and SAS are excellent."
"We have complete control over our data."
"It is not a pricey product compared to other data warehouse solutions."
"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."
"The solution has been reliable."
"It has allowed fast daily loads and analysis of millions of rows of data, which eventually moved to near real-time."
"The tool’s workflow is not user-friendly. It should also improve its orchestration monitoring."
"Data Factory could be improved in terms of data transformations by adding more metadata extractions."
"Azure Data Factory's pricing in terms of utilization could be improved."
"Azure Data Factory uses many resources and has issues with parallel workflows."
"The performance could be better. It would be better if Azure Data Factory could handle a higher load. I have heard that it can get overloaded, and it can't handle it."
"Occasionally, there are problems within Microsoft itself that impacts the Data Factory and causes it to fail."
"There is no built-in function for automatically adding notifications concerning the progress or outline of a pipeline run."
"It does not appear to be as rich as other ETL tools. It has very limited capabilities."
"We find the cost of the solution to be a little high."
"SQL installation is pretty tricky. The scalability and customer support also should be improved."
"I think that the error messages need to be made more specific."
"The reporting for certain types of data needs to be improved."
"In the future I would love to see a slightly better automation engine, just for the data integration layer, to make it slightly easier for end-users or junior developers to get involved in incremental updating."
"I would like the ability to do more real-time type updates instead of batch-oriented updates."
"More tools to help designers should be included."
"It could offer more development across the solution."
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Azure Data Factory is ranked 3rd in Cloud Data Warehouse with 81 reviews while Microsoft Parallel Data Warehouse is ranked 8th in Data Warehouse with 32 reviews. Azure Data Factory is rated 8.0, while Microsoft Parallel Data Warehouse is rated 7.6. The top reviewer of Azure Data Factory writes "The data factory agent is quite good but pricing needs to be more transparent". 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". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and Microsoft Azure Synapse Analytics, whereas Microsoft Parallel Data Warehouse is most compared with Microsoft Azure Synapse Analytics, Oracle Exadata, SAP BW4HANA, VMware Tanzu Greenplum and Snowflake. See our Azure Data Factory vs. Microsoft Parallel Data Warehouse report.
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