Azure Data Factory vs. BusinessObjects Data Integrator (discontinued)

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

Great tool for ETL with the ability to integrate with SAP products seamlessly. Supports Big data integration.

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

• Processing business validations on the input data set.
• Scheduling and notification using the Admin console tool.
• Code management across group of developers.
• Simple deployment process across environment.
• Ability to deploy stand alone jobs to automate task. Integration with OS and support for variety of data bases.

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

• Writing custom components is a complex process.
• Along with ETL BODI should have some data quality integration.
• Ready documentation of the code and inbuilt commenting on components.

Incentivized

It is a good ETL tool to use if you are SAP shop and looking for a simple and elegant solution for automation.

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 a good package tool with SAP BO set of product line

Incentivized

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

Incentivized

• It was a packaged purchase of BO toolset including BOXI and BODI.
• Optimized performance for integrating different data sources.
• Simple and easy setup and maintenance cost.

Incentivized