IBM Elastic Storage Server vs. IBM Storage Fusion

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.

Incentivized

I think its well suited for all modern programming. simple and ease of use are a plus.

Incentivized

• 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

• Connecting with multiple application DB of different data types and bringing the normalized data to on a roof/data lake
• Easy to build the models and analytics that's help better understanding of business operation
• AI models such as predictions, forecasts, and suggestions based on individual customer patterns or geo-clusters can build easily

Incentivized

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

Incentivized

• Improvement in areas where Software Defined Storage (SDS) can be better utilized with the broad capabilities of IBM storage features.
• Focus should be shifted towards enabling capabilities of cyber resiliency as the other offerings in the market are already equipped with the same.
• Broader non-IBM/Lenovo hardware support can be considered, specifically for IBM Storage fusion software offerings

Incentivized

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.

Incentivized

Incentivized

• 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.

• IBM Fusion is ideal for Enterprise businesses or Ecosystems where large data types are in play. And added benefit to bringing them under a platform to add visualization and understanding.
• Managing and monitoring is easy when compare to other industry tool

Incentivized