Azure Data Factory vs. Azure HDInsight

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: A tiny-mid sized company with no immediate plans of growing the volume of their data processing, that can afford long response times from support. Also it helps if you are not prone to put your hands on Linux and Spark configuration. In fact, it can make things go really faster if you also work with the bundle-in Jupyter. And, if you need to perform some diagnostics and / or administrative tasks, that's full of tools to find an understand the Root Cause. Ideal for non experts. Less appropriate: Big Data company, intense on demand cluster creation, mission critical, costs reduction, latest versions of libraries required, sophisticate customizations required.

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

• Data is presented without interfering others (IT or other dept).
• Data is managed properly and is available for retrievable any time.
• Legacy use of CD/DVD and Pendrive are not required.

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.

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• The only problem I have come across is when loading large volumes of data I sometimes get an error message, I assume this means something is corrupt from within. I would love a way for this to be resolved without having to start over.

Incentivized

Azure HDInsight is usable on the top of Azure Data Lake and gives us the benefit of analyzing large scale data workload in Hadoop. Usability and support from Microsoft are outstanding.

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

Inexpert, isolated teams... not good for support an excessively complex platform. Lots of weeks or months for a complex problem troubleshoot. Many time lost stuck on MindTree, before the case was finally escalated with Microsoft!

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

At this time I have not used any other similar products... I am open to it but Azure HDInsight and its components really work well for our organization.

Incentivized

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

Incentivized

• ROI is of course there, as no legacy software for data presentation.
• No manual intervention for data retrieval.
• Data is available anywhere as requested.

Incentivized