Azure Data Factory vs. CData DBAmp

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

Well suited as an inexpensive tool as "middleware" between your on-prem or hosted SQL Server. Not sure how well it will translate to cloud-based SQL as a platform (Azure SQL) as it relies on linked servers. This tool only applies to Salesforce CRM - not Marketing Cloud. For writing back to Salesforce we did run into Salesforce resource limitations when extensive triggers existed on the objects.

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 & Links to Salesforce CRM databases - including custom objects.
• Built in procedures to create copies of the database on SQL Server.
• Built in procedures to Add, Update, and Delete data within Salesforce CRM.
• Great Technical Support.

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

• Because it uses Linked Servers, not sure how this will work in Azure SQL.
• Replicated tables are based on user security - this means you have to pay for a license to set this up.
• There is no built-in function to skip tables or fields on secured tables. This has to be done on the CRM side for fields and we built a function to skip tables in the replication logic.

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

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

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

Incentivized

• Enabled automated marketing segments which enabled automated email series.
• Helped us solicit donations for the right amount at the right time.
• Helped us take on new marketing and fundraising campaigns without adding staff.

Incentivized