Azure Data Factory vs. ibi Data Migrator vs. Stitch Labs (discontinued)

Best scenario is for ETL process. The flexibility and connectivity is outstanding. For our environment, SAP data connectivity with Azure Data Factory offers very limited features compared to SAP Data Sphere. Due to the limited modelling capacity of the tool, we use Databricks for data modelling and cleaning. Usage of multiple tools could have been avoided if adf has modelling capabilities.

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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.

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• Data Ingestion - it works very well with numerous data sources.
• Data pipeline orchestration: It is a generic, popular tool for orchestrating data pipelines.
• Works well in Azure ecosystem, Azure services and data platforms like Databricks.
• It is a serverless and scalable solution for cloud data integration.

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

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• Granularity of Errors: Sometimes, Azure Data Factory provides error messages that are too generic or vague for us, making it challenging to pinpoint the exact cause of a pipeline failure. Enhanced error messages with more actionable details would greatly assist us as users in debugging their pipelines.
• Pipeline Design UI: In my experience, the visual interface for designing pipelines, especially when dealing with complex workflows or numerous activities, can become cluttered. I think a more intuitive and scalable design interface would improve usability. In my opinion, features like zoom, better alignment tools, or grouping capabilities could make managing intricate designs more manageable.
• Native Support: While Azure Data Factory does support incremental data loads, in my experience, the setup can be somewhat manual and complex. I think native and more straightforward support for Change Data Capture, especially from popular databases, would simplify the process of capturing and processing only the changed data, making regular data updates more efficient

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

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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.

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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.

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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

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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.

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Azure Data Factory helps us automate to schedule jobs as per customer demands to make ETL triggers when the need arises. Anyone can define the workflow with the Azure Data Factory UI designer tool and easily test the systems. It helped us automate the same workflow with programming languages like Python or automation tools like ansible. Numerous options for connectivity be it a database or storage account helps us move data transfer to the cloud or on-premise systems.

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

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• Facilitate better decision-making and improve business processes.
• Optimize business process outcomes by increasing internal efficiency and operational effectiveness.
• Boosts revenue growth while improving business process agility.

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• 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

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