Azure Data Factory vs. TIBCO Data Virtualization

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

TIBCO Data Virtualization is well suited for customers who are challenged to deal with extracting data from dozens of different sources and systems, and do not have the time and liberty to hire data engineers and/or ETL developers to write dozens or hundreds of complex ETLs. However, there are situations where TIBCO Data Virtualization severely underperforms, and those are where we are dealing with large volumes of data, in tera bytes or peta byte scale system. For example, a messaging queue which sends 200 million messages every hour will choke TIBCO Data Virtualization if the technology is chosen to route the data.

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

• Connecting to different data silos and presenting the data as a singled unified layer of data.
• Exposing data to Technical and non technical users through Web UI or reporting tools
• Secured exposure of data as web services.
• Row level and column level data security
• Multi tenancy data security.
• Real time data by connecting to the operational databases
• Historical data generation

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

• Performance of TDV Studio (its own IDE) is poor.
• Performance of TDV repository database is rather poor for larger numbers of objects .(Note: We have approx. 9tsd objects introspected in TDV and approx. 20tsd objects generated in upper DV layers.)
• Propagation of privileges to parent/child dependencies does not work when applying recursively on a folder. (It's a huge setback when working with large number of objects organized semantically into subfolders.)
• Lack of command line client interface for scripting at the time of version 8.4 (I had to write my own CLI.)
• TDV Studio does an absolutely horrible job with its own code editors when indentation is in place. Also, the editor is brutally slow and feature-poor.
• Tracking privileges on the level of table/view columns causes occasional problems when regranting.
• TDV's stored programs ("SQL scripts" in their own terminology) compiler leaves out many syntactic and semantic checks, making them hugely prone to run-time errors.
• TDV Server's REST API is a very poor (in terms of features) and flawed cousin to its SOAP API (at the time of version 8.4).

Incentivized

It is useful for us to see the data and do analysis. Also we use it to generate reports and see trends or gather insights

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

TDV's interface is a bit dated and not entirely intuitive. Would recommend some UX design review as the interface leaves a bit to be better understood to be used by users without inherent knowledge of Tibco. Overall I'd suggest more improvement here to ensure usability by a lesser tech audience.

Incentivized

We have never encountered issues where it was unavailable when we needed it.

Incentivized

This product's performance is very consistent. It is extremely rare for templates to fail. I've been using this software for 5 years and find it to be both simple and powerful. The impact within the company has been very positive as different processes in different areas, such as data analysis, development, and integrations, have been improved, and, best of all, it has not affected the users. Various systems with which it is connected in order to obtain information.

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

On a few occasions I have asked TIBCO technical support for help because I have adapted perfectly to their tools, but in those few that I have communicated with their technical team I have received personalized, attentive, responsible attention and I am always assisted by an expert staff the topic. A TIBCO technical support technician spent more than an hour helping me to solve a problem in the initial stage of implementation in my department and this is something that I always appreciate.

Incentivized

The training was helpful. I was able to understand how to use TIBCO for the data load process that we implemented and how to perform various troubleshooting steps based on the training I received. The technician was thorough and took the time to answer any questions. Once we were shown how to use TIBCO in the test environment, we were able to configure the production environment ourselves.

Incentivized

Other vendors have clearer, more visual implementation documentation. We also did not have our data architect and and server administrator available full-time for implementation. In the future, we will secure the necessary internal resources.

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

We did not need to evaluate another technology in the same category for data virtualization, since we are 100% sure of the capabilities and benefits that we would have with TIBCO Data Virtualization, both for market positioning as well as success stories from other companies. great renown worldwide. From the first day of use, it meets our needs to provide the expected solutions.

Incentivized

Good scaling

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 took spreadsheets that took hours a month to update and made them update automatically using TDV, saving hours a month of analyst time
• The incremental cost of TDV relative to straight spotfire licensing made it a no-brainer due to the ease of data management
• We continue to automate legacy business processes in TDV, saving time all over the organization.

Incentivized