HP StoreVirtual VSA was software defined storage, from HPE replacing the former LeftHand P4000 VSA. It reached EOL March 2019.
N/A
IBM Elastic Storage Server
Score 8.3 out of 10
N/A
IBM Elastic Storage Server (IBM ESS) is a software-defined storage option.
N/A
Pricing
HPE StoreVirtual VSA (Discontinued)
IBM Elastic Storage Server
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
HPE StoreVirtual VSA (Discontinued)
IBM Elastic Storage Server
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
—
More Pricing Information
Community Pulse
HPE StoreVirtual VSA (Discontinued)
IBM Elastic Storage Server
Considered Both Products
HPE StoreVirtual VSA (Discontinued)
No answer on this topic
IBM Elastic Storage Server
Verified User
Anonymous
Chose IBM Elastic Storage Server
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 …
We have used Cisco Cloud Object Storage earlier which is also a good object storage solution. COS has partnered with multiple vendors for object storage solutions and IBM storage solution is one of them. As far as the high performance of AI and Big Data applications is …
1. Perfect solution for geographically separated teams to work on sharing files/media. 2. Mainly suitable for CCTV/video recordings as the network speed and disk throughput is mammoth 3. Suites well for organizations looking for their own private cloud object storage solutions 4. primarily focused on hosting next-generation of applications centric to AI/IOT and ML.
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.