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 how you can create your own pipeline in your space and reuse those creations. You can collaborate with other people who want to use your code."
"The solution includes a feature that increases the number of processors used which makes it very powerful and adds to the scalability."
"The function of the solution is great."
"Feature-wise, one of the most valuable ones is the data flows introduced recently in the solution."
"For me, it was that there are dedicated connectors for different targets or sources, different data sources. For example, there is direct connector to Salesforce, Oracle Service Cloud, etcetera, and that was really helpful."
"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."
"It is easy to deploy workflows and schedule jobs."
"The overall performance is quite good."
"It handles large amounts of information with a linear performance increase, in relation to a HW investment."
"Auto-partitioning and indexing, and resource allocation on the fly are key features."
"Teradata is a great, industry-leading data warehousing product that has MPP architecture."
"I like this solution's ease of design and the fact that its performance is quite good. It is stable as well."
"It's very mature from a technology perspective."
"Cuts time to process huge amounts of data with efficient analytical queries."
"There are several features of Teradata that I like. One of the most basic is the indexes. I also like that it provides lower TCO. It also has the optimizer feature which is a good feature and isn't found in other legacy systems. Parallelism is also another feature I like in Teradata because when you are running or hosting on multiple systems, you have this shared-nothing architecture that helps. Loading and unloading in Teradata are also really helpful compared to other systems."
"It effectively has allowed us to remove over 20 portion copies of the data sets on other DB platforms for real-time operational reporting purposes."
"This solution is currently only useful for basic data movement and file extractions, which we would like to see developed to handle more complex data transformations."
"The need to work more on developing out-of-the-box connectors for other products like Oracle, AWS, and others."
"Currently, our company requires a monitoring tool, and that isn't available in Azure Data Factory."
"There is no built-in pipeline exit activity when encountering an error."
"The tool’s workflow is not user-friendly. It should also improve its orchestration monitoring."
"The user interface could use improvement. It's not a major issue but it's something that can be improved."
"Areas for improvement in Azure Data Factory include connectivity and integration. When you use integration runtime, whenever there's a failure, the backup process in Azure Data Factory takes time, so this is another area for improvement."
"Occasionally, there are problems within Microsoft itself that impacts the Data Factory and causes it to fail."
"Teradata should focus on functionality for building predictive models because, in that regard, it can definitely improve."
"We tried to use case Teradata for a data warehouse system, but we had some problems in relation to the Teradata system, CDC tools, and source databases. We were unable to transfer data from HPE Integrity mainframe to Teradata."
"Teradata hardly supports unstructured data or semi-structured data"
"The user interface needs to be improved."
"It would help to make scaling easier with a reduced cost. "
"I would like to see more integration with many different types of data."
"The solution could improve by having a cloud version or a cloud component. We have to use other solutions, such as Amazon AWS, Microsoft Azure, or Snowflake for the cloud."
"It's primarily designed for big projects and therefore, the pricing is pretty high. It's not suitable for smaller companies."
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.
