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IBM Elastic Storage Server

IBM Elastic Storage Server

Overview

What is IBM Elastic Storage Server?

IBM Elastic Storage Server (IBM ESS) is a software-defined storage option.

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Recent Reviews

global scalable file systems

9 out of 10
January 16, 2023
ESS is a robustly articulated architecture built mainly focusing on file sharing and reliability. We could able to overcome some major …
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Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

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Product Demos

Deploying IBM Spectrum Scale HDFS Transparency with pre-existing ESS cluster through Hortonworks

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Product Details

What is IBM Elastic Storage Server?

IBM Elastic Storage Server Technical Details

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Comparisons

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Reviews and Ratings

(4)

Reviews

(1-3 of 3)
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February 01, 2023

IBM ESS for AI and Big Data storage solution

Verified User
Engineer in Engineering
Computer Software Company, 1001-5000 employees
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Use Cases and Deployment Scope
IBM Elastic Storage is a highly available and highly scalable software based storage system for AI and Big Data. We had high performance use cases for our AI applications for an AI based product that we were building and IBM Elastic storage looked like a perfect solution.This service simplified the storage for Data and Model management and we were easily able to storage huge multiple types of data include images, natural language as well as structured datasets using this solution.
Pros and Cons
  • Very High Availability and Scalability
  • Works particularly well for AI and Big Data usecases
  • Easily unifies all sorts and types of Data
  • Integration with other Big Data Platforms like EMR and Databricks needed
  • May not be suitable for non AI related/Legacy usecases
  • Native support for structured relational datasets
Likelihood to Recommend
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.
Most Important Features
  • High scalability for AI and Big Data usecase
  • Integration with IBM Data platform
Return on Investment
  • Faster read/write data pipeline workloads
  • Faster time to load models from Storage
  • Improved inference time for models
Alternatives Considered
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.
Other Software Used
Amazon S3 (Simple Storage Service), Databricks Lakehouse Platform (Unified Analytics Platform)
January 16, 2023

global scalable file systems

Verified User
Professional in Information Technology
Oil & Energy Company, 10,001+ employees
Score 9 out of 10
Vetted Review
Verified User
Use Cases and Deployment Scope
ESS is a robustly articulated architecture built mainly focusing on file sharing and reliability. We could able to overcome some major challenges like sharing files across multiple teams located in different GEOS and seamlessly copying/migrating data across multi-site environments. In addition, we overcome one of the major hurdles of multiprotocol access and a perfect stack of affordable distributed storage array
Pros and Cons
  • 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 maintenance procedure is not straight forward, needs lots of steps/dependency on spectrum scale software
  • Should have an option to deliver as an bundled components under IBM, instead of individual components from different vendors
Likelihood to Recommend
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.
Most Important Features
  • Erasure Coding
  • Policy based tiering
  • Cyber secure lockable data and audit trailsGlobal sharing and collaboration
  • Global sharing and collaboration
Return on Investment
  • 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.
Alternatives Considered
Robost design based on powerful processor, which leverages the complete power of the system at a blaze speed
January 14, 2023

Best cloud storage solution for Big Data and AI

Verified User
Professional in Information Technology
Information Technology & Services Company, 1001-5000 employees
Score 8 out of 10
Vetted Review
Verified User
Incentivized
Use Cases and Deployment Scope
IBM Elastic Storage Server or IBM Elastic Storage Server is one of the best scalable, high-performance storage appliances available in the market. We are using IBM Elastic Storage Server for Big Data Application storage which needs on-demand scalability and high performance. IBM Elastic Storage Server is best suited for such purpose as it has reduced our maintenance and operational issues with the traditional on premise storage solution.
Pros and Cons
  • On demand high scalability
  • High performance specially for Big Data and AI Applications
  • Less operation and maintenance cost
  • Integration and configuration need a bit more technical expertise which is I guess expected.
  • There can be some improvement in integration with Legacy applications.
Likelihood to Recommend
The biggest challenges with Big Data Applications are scalability and performance. IBM Elastic Storage Server provides solutions for both of these challenges. With on-demand scalability, we can forecast the storage requirement better unlike in traditional storage solutions where we had to predict the storage requirement months before. Also, we get a lot more performance with IBM Elastic Storage Server as its spread across multiple nodes over the cloud which helps in fault tolerance also.
Most Important Features
  • Scalability
  • Reliability
  • High Performance
  • Better integration with other Appliances
Return on Investment
  • On demand scalability helped us in better projection of storage requirement
  • With reduced human resource for operation and maintenance of storage, ROI has been increased a lot.
  • High performance of Big Data applications using IBM Elastic Storage Server has improved the business.
Alternatives Considered
  • Cisco Cloud Object Storage (COS)
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 concerned, COS can't beat IBM Elastic Storage Server.
Other Software Used
Cisco Cloud Object Storage (COS), Dell ECS, Storage as a Service from Hitachi Vantara (STaaS)
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