Azure Data Factory vs. Talend Open Studio (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.

Incentivized

For quick daily integrations Talend is a very good tool and it makes development time so short and easy. Citizen developers who are not great programmers can pick up and start using Talend Open Studio within weeks. It's well suited for all kinds of data migration between various systems. It is less appropriate for smaller synchronous services where you need to trace the complete transaction and how data moved between them. It's also less appropriate for small data movements where other tools can be easier to use and manage.

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

• Your developers will be able to design SOA services graphically, and it is very easy to document and implement the code.
• Talend Open Studio is based on Eclipse IDE, so your developers will be very comfy using it
• Open is Key in Talend Open Studio = Open Source

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 community is not that up to date and forum is not that great in response. Probably we should make people aware of the tool more on how to use and its implementations.
• Talend crashes when transforming a lot of data (millions of rows).
• Proper training documentation is a must for talend which is currently lagging. This will help users to learn more about Talend and use it effectively.

Incentivized

There is no licence requirement for Talend Open Studio. So, this is not relevant question. However, if you are asking whether we will use Talend in future. Yes. We will continue to use it. It's very powerful free tool which caters to all our extra, transform, load capabilities. We just love Talend for it's great functionality and ease of use.

Incentivized

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

Talend Open Studio is based on Eclipse and is full of redundant procedures to do one thing, like when installing libraries. Sometimes I cannot manually download the libraries that it can't find.

Many times, Talend freezes. When you give a cancel command, it takes several minutes to stop. It also takes a great toll on our PC with 16 GB of ram and I7 CPU, even in idle status. If you are downloading Maven Jar/Libraries, you cannot do anything and have to wait until the task is finished.

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 Open Studio is free and we are not using the enterprise version which comes with licence and support. So, mostly depend on the open source community for any issues that we face. The document is good and we didn't have to use any support so far. We did evaluate the enterprise version and so far sticking to the free version.

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

Informatica has a limited number of components that you can use. This places a heavy limitation on the capabilities of Informatica. On the other hand, Talend allows you to create your own custom components using Java. For businesses that need to perform a wide variety of data operations, it can be quite useful to have the option of creating your own custom components to satisfy business needs.

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

• I delivered projects the client did not believe were possible, and I provided intermediate value by providing visibility to hidden data problems in their systems they could not detect before.
• I was able to work 3 projects at a time, pausing gracefully in one while switching to the other, with minimal effort.

Incentivized