Azure Data Factory vs. Make

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.

Incentivized

Integromat is the best tool for business automation in my opinion because unlike Zapier it allows us to integrate with any API even if the app is not available which allows us to create automation even with the less known apps that we use or the ones that we built internally for our own company.

Incentivized

• 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.

Incentivized

• UI/UX Simplicity and Features
• Workflows are explained in details and even people without IT background can use the tool.
• Consumption is nicely tracked.
• Myriad of existing templates, solutions, and readymade connectors.

• 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

Incentivized

• There are always new platforms and connections that we'd like to see
• More flexibility in paying for operations (tasks) on a sliding scale, instead of by tier
• More thorough support documentation on connecting various platforms and troubleshooting errors

Incentivized

At this point, it is firmly embedded in the DNA of the business and to give up the ability to automate workflows and create integrations on the fly would be a terrible idea.

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

Make's easy to understand user interface helps you to visualize what's happening at all times. Could use some tweaks around the navigation from a scenario specifically in the folders and back navigations. I can't tell you the amount of time wasted in that area. When you branch, you can't bring a branch back together in the same scenario which is kind of a bummer as well.

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

The pricing schema is very attractive, almost 50% lower than the competition. You could start from free and then grow. It has a pretty big library of connections to other apps and services, which really helps you when everything is a mess. Integromat has a really easy-to-use interface. You could do almost everything with fewer than 5 clicks. Scenarios (automation steps to complete a routine) have graphics so you can configure them more easily.

Incentivized

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.

Incentivized

Integromat allows us to do everything we used to do on Zapier but it doesn't limit us to only the popular apps, with Integromat we're integrating custom APIs and we get data from different servers through GET requests and it's exactly what we needed and Zapier couldn't provide it.

Incentivized

• 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.

Incentivized

• We used too many credits multiple times and had to buy them additionally, there are no prevention systems to setup to alert before it happens.
• Some consumption is difficult to understand and requires time and digging.
• It requires heavy internal effort to simplify things in Make in order for it to operate cheaper.
• Initial IT setup is paramount and determines a lot.