We performed a comparison between Azure Data Factory and IBM Db2 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."Powerful but easy-to-use and intuitive."
"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."
"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."
"The trigger scheduling options are decently robust."
"I am one hundred percent happy with the stability."
"The best part of this product is the extraction, transformation, and load."
"It makes it easy to collect data from different sources."
"I like the basic features like the data-based pipelines."
"The analytics engine is not bad at forecasting predictions."
"I think it scales really well and as long as you take enough time to learn a little bit about it, it works really well."
"The standout feature of IBM Db2 Warehouse, which is particularly valuable for large enterprises, is its ability to handle big data."
"Some of the best features are stored procedures, parallelism, and different indexing strategies."
"Provides good security and reliability."
"It can be mounted on the cloud, which is a huge plus. If the client, for example, starts small with on-premise deployment and then it rapidly needs to grow, we can transfer this to the cloud easily."
"Azure Data Factory could benefit from improvements in its monitoring capabilities to provide a more robust feature set. Enhancing the ease of deployment to higher environments within Azure DevOps would be beneficial, as the current process often requires extensive scripting and pipeline development. It is also known for the flexibility of the data flow feature, particularly in supporting more dynamic data-driven architectures. These enhancements would contribute to a more seamless and efficient workflow within GitLab."
"The solution needs to be more connectable to its own services."
"The support and the documentation can be improved."
"The tool’s workflow is not user-friendly. It should also improve its orchestration monitoring."
"The product's technical support has certain shortcomings, making it an area where improvements are required."
"Azure Data Factory can improve by having support in the drivers for change data capture."
"Sometimes I need to do some coding, and I'd like to avoid that. I'd like no-code integrations."
"The solution should offer better integration with Azure machine learning. We should be able to embed the cognitive services from Microsoft, for example as a web API. It should allow us to embed Azure machine learning in a more user-friendly way."
"In terms of improvement, IBM Db2 Warehouse should be more scalable."
"The biggest problems we have is when the backup solution is failing or slow and we run out of log space, which has happened probably a couple of times in the last four years."
"IBM Db2 Warehouse needs to improve its interface."
"Lacks sufficient documentation and particularly in Spanish."
"The biggest challenge anyone could have with Db2 Warehouse is their references or online resources and documentation. They are very, very, very limited on the web."
"There should be more material available for training and training should be free."
"The areas of the solution that is needing the most improvement are separating compute from storage, elasticity, which means scaling up and then retracting."
Azure Data Factory is ranked 3rd in Cloud Data Warehouse with 81 reviews while IBM Db2 Warehouse is ranked 14th in Data Warehouse with 8 reviews. Azure Data Factory is rated 8.0, while IBM Db2 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 IBM Db2 Warehouse writes "Useful for ETL process and has good documentation ". Azure Data Factory is most compared with Informatica PowerCenter, Informatica Cloud Data Integration, Alteryx Designer, Snowflake and Microsoft Azure Synapse Analytics, whereas IBM Db2 Warehouse is most compared with Oracle Exadata, Snowflake, Amazon Redshift, Apache Hadoop and IBM Netezza Performance Server. See our Azure Data Factory vs. IBM Db2 Warehouse 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.
