Azure Blob Storage, with Azure Data Lake Storage vs. Azure HDInsight

In Azure, it is the storage to use, and in my view, the Blob Storage offers more, or finer-grained configuration options, than S3. So my recommendation would be to check in detail what is offered. As the Blob Storage is more or less a Microsoft exclusive product, the "interoperability" is more limited than, for example, with S3. The S3 is more widely adopted, and if you cannot exclude a migration scenario from one cloud provider to another, additional effort is needed.

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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.

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• The data lake analytics tool is good and provides loads of computing power to speed up the processing time.
• It provides unlimited storage for structured, semi-structured or unstructured data.
• Cloud-based service and we can easily use it for ETL and ELT processes.

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• 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.

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• study for the certifications also to have them as a reference for work when you have any questions about applying a configuration to the equipment.
• The Internet interface is simple and easy to use. Capacity is good and it's good that HP continues to innovate with this technology

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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.

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Blob storage is fairly simple, with several different options/settings that can be configured. The file explorer has enhanced its usability. Some areas could be improved, such as providing more details or stats on how many times a file has been accessed. It is an obvious choice if you're already using Azure/Entra.

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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.

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Microsoft has improved its customer service standpoint over the years. The ability to chat with an issue, get a callback, schedule a call or work with an architecture team(for free) is a huge plus. I can get mentorship and guidance on where to go with my environment without pushy sales tactics. This is very refreshing. Typically support can get me to where I need to be on the first contact, which is also nice.

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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!

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Azure Premium Blob offers better latency than competitors. It works best with the Azure ecosystem, and competitors lack it. Azure Blob even stands out in storage durability, providing up to 16 nines. It can have various use cases that can suit all the organisation's needs. The Azure Blob solution can also be deployed on-premises.

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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.

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• Data Migration projects from relational sources to Azure Data Lake Storage have given a great ROI, thanks to the less running costs, and High availability
• Pretty easy to work with in terms of Managing and accessing Data in containerized fashion.
• Further features like Archival of data which is accessed less frequently can significantly reduce cost

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

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