Azure Blob Storage vs. Azure Data Factory

Azure Blob Storage is well suited for cases where you are working with different data formats and looking for cost-effective storage solutions based on access frequency. Another area of strength is the encryption of data at rest, and encryption can be managed on your own. However, it may not be appropriate for transferring large data very fast.

Incentivized

In a data pipeline, you will be able to add different kinds of activities for example connect from your on-premise SFTP and move CSV files to storage accounts. As well data factory has its own data flow if you are an ETL developer who experimented with maybe you have worked with SSIS, thus, you will start quickly with this new feature of the data factory.

Incentivized

• Reduced cost. We were able to reduce our storage infrastructure by several hundred terabytes by consolidating redundant copies and dedupe/compression on files.
• Extremely high level of redundancy. We can replicate data in a variety of ways that we would never have been capable of on our own hardware.

Incentivized

• Creating ETL and ELT workflows as well as orchestrating and monitoring pipelines without writing any code.
• Hybrid data integration is easily and agilely possible through this software.
• It has lot of various useful components

Incentivized

• If we are transferring huge amount of data (outbound), it can get quite expensive.
• With new features being added constantly, although a good thing, at times it becomes difficult to keep up with the changes. Documentation needs to keep UpToDate and should include best practices.
• Performance can be improved especially when it comes to cold storage.

Incentivized

• Learning curve for pipeline creation interface.
• Alerting isn't necessarily built in. Had to work around this to meet team needs.
• With GIT enabled, some features can only be done via git, while some need to be done via the portal.

Incentivized

Blob storage is fairly simple, with several different options/settings that can be configured. The file explorer has enhanced its usability. Some areas could be improved, such as providing more details or stats on how many times a file has been accessed. It is an obvious choice if you're already using Azure/Entra.

Incentivized

So far product has performed as expected. We were noticing some performance issues, but they were largely Synapse related. This has led to a shift from Synapse to Databricks. Overall this has delayed our analytic platform. Once databricks becomes fully operational, Azure Data Factory will be critical to our environment and future success.

Incentivized

Documentation sometimes appears to be out of date or not fully documented properly with new releases. It is like documentation comes out for a specific version and is quickly out of date. Another issue is documentation is scarce on new releases and only seems to get properly updated (and sometimes is still wrong) once enough people hit the forums to complain.

Incentivized

We have not had need to engage with Microsoft much on Azure Data Factory, but they have been responsive and helpful when needed. This being said, we have not had a major emergency or outage requiring their intervention. The score of seven is a representation that they have done well for now, but have not proved out their support for a significant issue

Incentivized

Blob storage lets us control the file source/hosting and retain everything within our Microsoft ecosystem. Blob is less feature-rich than some of the other products. Still, we consider it as a value-added product included within our environment, and alternative products are not needed for our requirements. Keeping the hosting within our tenant locale is vital to us.

Incentivized

Azure Data Factory fits well into our overall systems architecture where we already utilize largely Azure services and also Microsoft based products in the on-premises environment. I think cost structure is also very competitive with Azure Data Factory. Most services provide a visual interface for designing ETL workflows, but our team found Azure Data Factory's interface more intuitive.

Incentivized

• Made it easy for organization to move to cloud from on-premise based solution.
• We were able to centralize all our documents.
• Cost savings compared to on-premise based solutions.

Incentivized

• Limiting the amount of data moving up and down from the cloud for cloud-native applications.
• Overall simple to use interface which is actually easier for a first time ETL developer than SSIS.

Incentivized