Azure Data Factory vs. Talend Data Fabric

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

Truly trusted contact center where the effective solution is always guaranteed. It is not a one-off fix to a specific data integration or management problem. It is a permanent and scalable solution to manage all of your data under a unified environment. Easy to use, great performance, used it for our internal data warehouse. Easy to build and connect to our data sources such as Salesforce, Netsuite, and Marketo.

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

• It supports a wide variety of connectors (Systems/endpoints)
• It provides great flexibility for developers as it not only has a lot of predefined ready to use the function but also provides the ability to use complex java code within the platform. Great tool if you have good developers available.

Incentivized

• 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

• The print and export functionality are missing in the Community version which frustrates a lot of our clients as well as internal users.
• The learning curve is very steep for all Talend products including DQ.
• Lack of easy to create workflows for jobs that can be repeated.

Lack of report export and publication! Steep learning curve!

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

At this moment the usability of Talend Data Quality is optimal, too bad I cannot say the same in the first three months, it was always a problem due to its steep learning curve, but what matters is being able to use it effectively at this precise moment.

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

Talend Data Quality gave us direct help in the learning process and prevented us from taking many more months to adapt and I appreciate this from the heart, I think that thanks to the support we can have very detailed reports that help increase the use of Talend Data Quality in the company.

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

The engine with which it works to process a lot of information is striking, the comparison also being the connectors it has for different RDBMS, which other tools do not count as they are GNU licenses or community editions. The friendly and intuitive environment is what catches the eye. that's why I choose Talend over any other tool

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

• Definitely simplified the development efforts on our end in doing the data integration, saving lots of human hours.
• Small company, so cost could be a problem for these services, but works so far.

Incentivized