Azure Data Factory vs. CloverDX

Well-suited Scenarios for Azure Data Factory (ADF): When an organization has data sources spread across on-premises databases and cloud storage solutions, I think Azure Data Factory is excellent for integrating these sources. Azure Data Factory's integration with Azure Databricks allows it to handle large-scale data transformations effectively, leveraging the power of distributed processing. For regular ETL or ELT processes that need to run at specific intervals (daily, weekly, etc.), I think Azure Data Factory's scheduling capabilities are very handy. Less Appropriate Scenarios for Azure Data Factory: Real-time Data Streaming - Azure Data Factory is primarily batch-oriented. Simple Data Copy Tasks - For straightforward data copy tasks without the need for transformation or complex workflows, in my opinion, using Azure Data Factory might be overkill; simpler tools or scripts could suffice. Advanced Data Science Workflows: While Azure Data Factory can handle data prep and transformation, in my experience, it's not designed for in-depth data science tasks. I think for advanced analytics, machine learning, or statistical modeling, integration with specialized tools would be necessary.

Incentivized

CloverDX designer as a standalone is well suited for fairly straightforward transformations of data. If you want to do large scale data integrations, then their server edition adds an extra level of automation and job control.

Incentivized

• It allows copying data from various types of data sources like on-premise files, Azure Database, Excel, JSON, Azure Synapse, API, etc. to the desired destination.
• We can use linked service in multiple pipeline/data load.
• It also allows the running of SSIS & SSMS packages which makes it an easy-to-use ETL & ELT tool.

Incentivized

• Connects with Salesforce very well
• The graphical view of the transformations allows for easy creations and maintenance
• Support has always been eager to assist with any graph creation difficulties I run into

Incentivized

• Limited source/sink (target) connectors depending on which area of Azure Data Factory you are using.
• Does not yet have parity with SSIS as far as the transforms available.

Incentivized

• The initial learning curve is a little steep. Not very steep or super steep, just a little steep.
• Having enough memory for large multi-step problems can be an issue if the graph isn't designed 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

While CloverDX has an active forum for users to submit questions and assist with answers, their in house support team is incredibly responsive when I've contacted them for assistance. This seems almost at odds with most other software companies who try to save money on tech support by promoting a forum or knowledge base.

Incentivized

The easy integration with other Microsoft software as well as high processing speed, very flexible cost, and high level of security of Microsoft Azure products and services stack up against other similar products.

Incentivized

CloverDX was a less expensive alternative to Talend and had a more intuitive interface from what I could see during the evaluation.

Incentivized

• It is very useful and make things easier
• Debugging can improve
• Its better suited than other products with the same objective

Incentivized

• Work that use to take multiple people 20 to 30 hours a week to complete each has now been fully automated to where only 1 or 2 hours a week for maintenance is required.

Incentivized