IBM Elastic Storage Server vs. Nasuni

Reliable data storage and access is a big challenge in AI applications and IBM ESS is a service you need to solve the problem. If you are building an AI service and you already use the IBM ecosystem for AI compute requirements, ESS can serve as an excellent software based storage solution. Integration with other platforms such as EMR/Databricks is still a challenge and should be improved.

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Well suited if you have a lot of data that doesn't need to be stored and read right away. I think even if you don't have much data, you can still use it for it's intended purpose to great effect, but think of it as the more data you have, the even better it will work. I don't think it would be particularly useful if you already have a slick file restore system in place and you don't need to store your data elsewhere with redundancy.

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• Powerful processing power, literally support unlimited scale out storage capabilities
• well integrated and supported with multi flavor environment and file systems.
• Huge capacity with in a very reduced form factor of disks/enclosures

• The management console is extremely simple and easy to navigate, making common tasks easy to do.
• Our storage appliance is configured to snapshot data several times an hour, making the risk of data loss very low.
• Data restores are very intuitive, and take seconds to initiate regardless of whether it is one file or 300GB of data. We have successfully restored many Gigs of data in minutes.

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• Integration and configuration need a bit more technical expertise which is I guess expected.
• There can be some improvement in integration with Legacy applications.

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• Better analytics when issues arise.
• Better onboarding documentation.
• Real-time monitoring.

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As I mentioned, the user interface is amazing and straight forward. It's very easy to learn how to configure and restore files. I would like a bit more reporting, especially in terms of live reporting and monitoring. The support is great when you have a question on how to do something, which helps with usability.

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Again, it may have a little to do with the size and speed of your own environment, but we've been nothing but pleased with the speed of access of the files - even pulling old files from the cloud storage. Recovery of huge and many data files is a bit slow if you don't have the specs of the filer up to snuff.

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IBM ESS is optimized for AI and Big Data usecases while S3 is a general purpose storage solutions. EMR and Databricks have lakehouse/data warehousing solutions for distributed computing but are more optimized for just the big data pipelining solutions and not essentially for AI usecases, especially for inference, when you need to load model artifacts really quickly.

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The technical support and escalation path for Nasuni is much more reliable and efficient. No getting transferred to various teams. Often times, the person who answers your call is able to resolve your issue. If they cannot, they get the case assigned to the appropriate engineer right away. Time to close has always been very good.

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• When the cost and price dynamics comes into account, we have replaced age old traditional arrays with almost negligible cost with ESS
• able to extend the capabilities of global teams to work and share their experiences and knowledge with other teams.

• Dramatically reduced time spent managing our storage platform. Quotas and reporting tools take all the guesswork out of data growth. Updates are easy to deploy. Time freed up can be used for more user-facing activities that we consider more valuable to the organization.
• The overall stability of the platform has been very good. We have been running on the same hardware for the past four years without any performance issues.

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