Azure Data Factory vs IBM Db2 Warehouse comparison

"The most valuable features are data transformations."

"We haven't had any issues connecting it to other products."

"The most valuable feature of this solution would be ease of use."

"The feature I found most helpful in Azure Data Factory is the pipeline feature, including being able to connect to different sources. Azure Data Factory also has built-in security, which is another valuable feature."

"It makes it easy to collect data from different sources."

"Data Factory's best features include its data source connections, GUI for building data pipelines, and target loading within Azure."

"This solution has provided us with an easier, and more efficient way to carry out data migration tasks."

"ADF is another ETL tool similar to Informatica that can transform data or copy it from on-prem to the cloud or vice versa. Once we have the data, we can apply various transformations to it and schedule our pipeline according to our business needs. ADF integrates with Databricks. We can call our Databricks notebooks and schedule them via ADF."

"It can scale effectively as long as resources are available."

"Provides good security and reliability."

"Some of the best features are stored procedures, parallelism, and different indexing strategies."

"IBM Db2 Warehouse is more resilient when dealing with business intelligence applications."

"The standout feature of IBM Db2 Warehouse, which is particularly valuable for large enterprises, is its ability to handle big data."

"The analytics engine is not bad at forecasting predictions."

"The solution is stable."

"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."

"It does not appear to be as rich as other ETL tools. It has very limited capabilities."

"Azure Data Factory can improve by having support in the drivers for change data capture."

"Azure Data Factory's pricing in terms of utilization could be improved."

"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."

"A room for improvement in Azure Data Factory is its speed. Parallelization also needs improvement."

"It's a good idea to take a Microsoft course. Because they are really helpful when you start from your journey with Data Factory."

"I would like to be informed about the changes ahead of time, so we are aware of what's coming."

"I rate Azure Data Factory six out of 10 for stability. ADF is stable now, but we had problems recently with indexing on an SQL database. It's slow when dealing with a huge volume of data. It depends on whether the database is configured as general purpose or hyperscale."

"There were some initial challenges with IBM Db2 Warehouse about eight months ago when I worked in this environment. When I coordinated with IBM support, they mentioned that the memory was insufficient for our needs. Our business environment required significantly more memory than the previous cluster could provide. Consequently, we have worked closely with on-site IBM technical personnel to address this issue."

"The primary challenges customers face with IBM Db2 Warehouse are related to its complexity in usage. It requires highly skilled professionals who understand Db2, and both training and support are challenging to obtain."

"In terms of improvement, IBM Db2 Warehouse should be more scalable."

"The primary challenges customers face with IBM Db2 Warehouse are related to its complexity in usage. It requires highly skilled professionals who understand Db2, and both training and support are challenging to obtain."

"Lacks sufficient documentation and particularly in Spanish."

"There should be more material available for training and training should be free."

"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."

"It takes a long time to have a new version or release, similar to Oracle."

"The price is fair."

"There's no licensing for Azure Data Factory, they have a consumption payment model. How often you are running the service and how long that service takes to run. The price can be approximately $500 to $1,000 per month but depends on the scaling."

"The price you pay is determined by how much you use it."

"The pricing is a bit on the higher end."

"In terms of licensing costs, we pay somewhere around S14,000 USD per month. There are some additional costs. For example, we would have to subscribe to some additional computing and for elasticity, but they are minimal."

"Understanding the pricing model for Data Factory is quite complex."

"This is a cost-effective solution."

"Our licensing fees are approximately 15,000 ($150 USD) per month."

"In a traditional on-prem database, in a data warehouse, the solution is probably on the expensive side."