Azure Data Factory vs. Fivetran vs. SolarWinds Task Factory

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

Fivetran's business model justifies the use-case where we require data from a single source basically a lot of data but if the requirement is not on the heavier side, Fivetran comes to costly operation when compared to its peers. Otherwise, I'll recommend Fivetran for stability and update and seamless service provider.

Incentivized

Since I started working with this great tool all data analysis programs have been running effectively. Implementation of projects and tasks have been effective and reliable. Data collected from each department gives us working plan on better management of various programs. The Dimension Merge SCD Transform helps us to load large volumes of data within a short period of time.

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

• Easily connects to source data using delivered connectors
• Transforms data into standard models and schemas
• Has very good documentation to help quickly setup connectors

Incentivized

• The single most beneficial component to Task Factory is the Upsert component. If you're familiar with writing MERGE statements in T-SQL, you'll appreciate the Upsert component. Drag the component into your Data Flow and a few clicks later you have a MERGE without the code complexities.
• Where some native SSIS components leave you wanting more, Task Factory extends on many of these components as well as support for data sources not native to SSIS components.
• The number of extra components that come in the Task Factory tool kit will expand your tool belt to do just about anything you need or want to accomplish in SSIS.

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

• Very difficult to get connectors enhanced if a specific needed object is not supported by them
• Depending on the edition needed and the data volumes, can get quite expensive

Incentivized

• It was built by Pragmatic Works who sold it to SentryOne and now Solar Winds, concerned about future support. SolarWinds is discontinuing support for related products such as BiXpress.
• Had issues with connecting to certain versions of SQL Server - would fail when deploying one package - had to deploy the entire solutions.
• Occasional random failures observed with the Filter tranform.

Incentivized

Task Factory has become a key product for our use of doing ETL work in SSIS. Their custom SSIS components allow us to work simply on the data engineering side of things. We can ignore the lower level work needed to connect to disparate data sources. This allows us to work faster and provide more value to the business

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

Very easy and intuitive to setup and maintain as there usually are not that many options. Very well documented (e.g. how to setup each connector, how the schema looks like, any specific features of this connector etc.). Also the operation is intuitive, e.g. you have status pages, log pages, configuration pages etc. for each connector.

Incentivized

Compared to some of the other transformations I have worked with, it really is pretty simple for the type of functionality you get

Incentivized

It runs pretty well and gets our data from point A to point cluster quickly enough. Honestly, it's not something I think about unless it breaks and that's pretty rare.

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

Overall, the best vendor we currently have on the data side of the house. No issues, issues are resolved very quickly and upgrades go without any issues.

Incentivized

Overall it went smoothly. Had a couple of gotchas with licensing and upgrading but nothing that really stopped us.

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 never seriously considered using anything else. Our data engineers had used Fivetran extensively in previous roles so when it came time to make a decision, there wasn't much of a process. They gladly signed the contract with Fivetran pretty quickly.

Incentivized

ZappySys is an alternative provider that we tested. However, we found the ease of use, set up and installation to be much simplier and quicker using Task Factory. ZappySys has a number of the same connectors but are more difficult to setup and the GUI is not as intuitive and simple to use.

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

• It has been very positive in serving BI team with new source requests
• It has been OK at scaling to match as data volumes as source data size grows

Incentivized

• We were able to support our developers with Task Factory features and reduce the development time by 40%.
• Recently Task Factory has changed their pricing module and it seems to be pretty costly for our process. Our business team has started to evaluate whether this is worth it going forward.

Incentivized