Azure Data Factory vs. Layer2 Cloud Connector

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

We had a scenario where our clients have thousands of external party vendors/committees who regularly sync SharePoint data. Managing thousands of external parties can never be possible without using a Layer2 cloud connector. We managed the local network sharing and SharePoint integration by using the Layer2 connector. Layer2 is convenient with a large amount of data as the per-user license is high.

• 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

• Layer2 provides best connectivity with SharePoint
• It syncs local network shared files to the SharePoint
• Provides details file history

• 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

• Per User cost is expensive
• A lot of pre-requisites
• UI needs to be more user-friendly

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

We had also used Microsoft One Drive as a syncing tool but it requires Office365 for managing and syncing data across thousands of vendors which was not practically possible to manage users on Office 365. Layer2 resolved this issue by having 3 user licenses and they are enough to periodically sync all external parties' data with our SharePoint online.

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

Incentivized

• Layer2 resolves the time management issue
• Resolved data syncing issues across different external vendors
• LOE optimisation with using Layer2 connector.