Microsoft's Azure Data Factory is a service built for all data integration needs and skill levels. It is designed to allow the user to easily construct ETL and ELT processes code-free within the intuitive visual environment, or write one's own code. Visually integrate data sources using more than 80 natively built and maintenance-free connectors at no added cost. Focus on data—the serverless integration service does the rest.
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SnapLogic
Score 8.5 out of 10
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SnapLogic is a cloud integration platform with a self-service capacity supported by over 450 prebuilt modifiable connectors. SnapLogic also offers real-time and batch integration processes for interfacing with external data sources, a drag-and-drop interface, and use of the vendors’ Iris AI.
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.
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.
Snaplogic is unique from other IPASS tools if you're very sensitive about data security as they have an on-premise option where your data never needs to leave your data center. And data pipelines can be quickly created if Snaplogic has the requisite connector to your data sources. On the downside, if you're transforming a large amount of data for example in training machine learning models, a tool with elastic compute capability is more appropriate.
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
This has been hands down the BEST software company I have ever used and dealt with. I am a 25 year IT veteran at this college. They go above and beyond in soliciting our feedback/input and proactively follow up about bugs, issues, etc. I have given multiple potential clients my thoughts and after seeing the SL demo they all sign up. I appreciate their support model, it's REFRESHING!
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.
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
They can be prompt but they have not been as useful as I've wanted. We had a bug that affected many of our customers through an API connection between SnapLogic and our platform. Eventually they were able to figure it out, but it took a long time of negotiating between our engineering team and theirs. Additionally, we installed the SnapLogic groundplex for our customers and we've run into a bunch of problems of connectivity. If SnapLogic offered to be on those calls with our clients to troubleshoot how to fix these problems, I would give them a better grade here.
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.
We opted for SnapLogic due its ease of use and the flexibility it offers, it was the platform that was strongest in both application integration and data integration and both were use cases we wanted to be able to cover.
