Azure Data Factory vs. Integrate.io

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

Integrate.IO or formerly XPlenty can be used for various needs:

• Multiple Sources (Excel, CSV, Text File, Blank File Type, All SQL Type)
• Multiple End Points (All SQL Type)
• Integration to Salesforce Sales Cloud
• Re-using the same package in different platforms which result to less development
• Value for the money

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

• Collecting data from different sources and making these available for BI tools or other IT systems.
• Their support department is really helpful when you are facing issues. Sometimes they refer to their documentation and sometimes they can help you right away.
• Generally I’m really happy with the ease of use. The software just does its job very well and we’re really getting a lot of value from it.

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

• It's not always easy to use.
• Debugging can be challenging when error logs lack specificity.
• Interaction between fields or packages is slow.

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

I found them super cool and helpful in any regarding to implementation.

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

Integrate.io offers more customization options than Datorama, allowing businesses to create their own custom integrations and workflows using their API and SDKs. Integrate.io's pricing model is based on the number of data transactions, which may be more cost-effective for businesses that have a high volume of data.

Incentivized

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

Incentivized

• Faster development with less skill requirements
• Part of long range planning
• Captured the data privacy requirements

Incentivized