Azure Data Factory vs. Stitch Labs (discontinued)

Well-suited Scenarios for Azure Data Factory (ADF): When an organization has data sources spread across on-premises databases and cloud storage solutions, I think Azure Data Factory is excellent for integrating these sources. Azure Data Factory's integration with Azure Databricks allows it to handle large-scale data transformations effectively, leveraging the power of distributed processing. For regular ETL or ELT processes that need to run at specific intervals (daily, weekly, etc.), I think Azure Data Factory's scheduling capabilities are very handy. Less Appropriate Scenarios for Azure Data Factory: Real-time Data Streaming - Azure Data Factory is primarily batch-oriented. Simple Data Copy Tasks - For straightforward data copy tasks without the need for transformation or complex workflows, in my opinion, using Azure Data Factory might be overkill; simpler tools or scripts could suffice. Advanced Data Science Workflows: While Azure Data Factory can handle data prep and transformation, in my experience, it's not designed for in-depth data science tasks. I think for advanced analytics, machine learning, or statistical modeling, integration with specialized tools would be necessary.

Incentivized

I can't recommend Stitch Labs as it was discontinued as of June 2021 (after being purchased by Square). All existing users have had to move off the platform and it they are not taking new customers. Square has said they are going to relaunch a new version of Stitch Labs possibly sometime in the future, but release date and features have not been announced.

Incentivized

• It allows copying data from various types of data sources like on-premise files, Azure Database, Excel, JSON, Azure Synapse, API, etc. to the desired destination.
• We can use linked service in multiple pipeline/data load.
• It also allows the running of SSIS & SSMS packages which makes it an easy-to-use ETL & ELT tool.

Incentivized

• Inventory management.
• Order management.
• Reporting and analytics.

Incentivized

• Limited source/sink (target) connectors depending on which area of Azure Data Factory you are using.
• Does not yet have parity with SSIS as far as the transforms available.

Incentivized

• Reporting does not work for multiple currencies.
• There is often a lag when syncing products.

Incentivized

I think the usability of SL is seamless comparable to other systems that we have and still have. I think the user interface could be better in some aspects, but also has improved the way we do business. Once you get around the brief learning curve SL tends to be easy to use and navigate.

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

We originally had phone support but when Stitch Labs updated the pricing they removed phone support from our service tier. It was very frustrating. We used their email contact and the answers were fine but sometimes it takes too long to try to solve something over email when you want to just talk to someone and get a quick answer.

Incentivized

The easy integration with other Microsoft software as well as high processing speed, very flexible cost, and high level of security of Microsoft Azure products and services stack up against other similar products.

Incentivized

I have not researched other alternatives as this solved my problems.

Incentivized

• It is very useful and make things easier
• Debugging can improve
• Its better suited than other products with the same objective

Incentivized

• We had to migrate off this system which was not ideal after being discontinued
• Was a simple to use medium price range solution to scaling businesses
• UI/UX was intuitive and was easy to train employees

Incentivized