We performed a comparison between Azure Data Factory and Teradata 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."I like its integration with SQL pools, its ability to work with Databricks, its pipelines, and the serverless architecture are the most effective features."
"It has built-in connectors for more than 100 sources and onboarding data from many different sources to the cloud environment."
"On the tool itself, we've never experienced any bugs or glitches. There haven't been crashes. Stability has been good."
"The security of the agent that is installed on-premises is very good."
"It is beneficial that the solution is written with Spark as the back end."
"Data Factory's best feature is the ease of setting up pipelines for data and cloud integrations."
"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."
"Improved performance of ETL procedures, reporting."
"It is a stable program."
"Their extensive experience in data warehousing, the platform's performance, and their strong reputation in the market are the most valuable."
"The most valuable feature of Teradata is security. It runs on Unix and Linux platforms which provide better security."
"Teradata has good performance, the response times are very fast. Overall the solution is easy to use. When we do the transformation, we have all of our staging and aggregation data available."
"Parallel processing features have helped to easily dump any size of data and retrieve data with great performance."
"The most valuable features are the large volume of data and the structuring of the data to optimize it and get very optimal data warehouse solutions for customers."
"The ability to handle machine data parallel processing is the most valuable feature of Teradata."
"Azure Data Factory can improve the transformation features. You have to do a lot of transformation activities. This is something that is just not fully covered. Additionally, the integration could improve for other tools, such as Azure Data Catalog."
"One area for improvement is documentation. At present, there isn't enough documentation on how to use Azure Data Factory in certain conditions. It would be good to have documentation on the various use cases."
"Data Factory's performance during heavy data processing isn't great."
"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's pricing in terms of utilization could be improved."
"The solution needs to be more connectable to its own services."
"The deployment should be easier."
"There should be a way that it can do switches, so if at any point in time I want to do some hybrid mode of making any data collections or ingestions, I can just click on a button."
"Teradata needs to expand the kind of training that's available to customers. Teradata only offers training directly and doesn't delegate to any third-party companies. As a result, it's harder to find people trained on Teradata in our market relative to Oracle."
"Teradata can improve the way it handles big data and unstructured data."
"Teradata should focus on functionality for building predictive models because, in that regard, it can definitely improve."
"Teradata's UI could be more user-friendly."
"GUI of administrative tools is really outdated."
"The scalability could be better. The on-premises solution is always more complicated to scale."
"Teradata is an expensive tool. Like, if you're already using Microsoft products like Windows, they'll market all their products together. And with the rise of cloud technologies, companies will adopt solutions that offer them some privileges or facilities. Similar to how SAP does it in the market, so do Microsoft and other companies. Even Oracle and other such tools are quite commonly seen compared to Teradata's competitors in everyday solutions."
"An additional feature I would you like to see included in the next release, is that it needs to be more cloud-friendly."
Azure Data Factory is ranked 3rd in Cloud Data Warehouse with 81 reviews while Teradata is ranked 3rd in Data Warehouse with 54 reviews. Azure Data Factory is rated 8.0, while Teradata is rated 8.2. 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 Teradata writes "Offers seamless integration capabilities and performance optimization features, including extensive indexing and advanced tuning capabilities". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and IBM InfoSphere DataStage, whereas Teradata is most compared with SQL Server, Snowflake, Oracle Exadata, MySQL and BigQuery. See our Azure Data Factory vs. Teradata report.
See our list of best Cloud Data Warehouse vendors.
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.
