HPE Cloud Volumes vs. IBM Data Replication

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
HPE Cloud Volumes
Score 7.6 out of 10
N/A
HPE Cloud Volumes is an enterprise grade multicloud storage solution supporting replication data storage at a monthly per usage cost.N/A
IBM Data Replication
Score 9.3 out of 10
N/A
The IBM Data Replication portfolio provides log based change data capture with transactional integrity to support big data integration and consolidation, warehousing and analytics initiatives at scale.N/A
Pricing
HPE Cloud VolumesIBM Data Replication
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
HPE Cloud VolumesIBM Data Replication
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Best Alternatives
HPE Cloud VolumesIBM Data Replication
Small Businesses
Hornetsecurity VM Backup
Hornetsecurity VM Backup
Score 8.4 out of 10
Hornetsecurity VM Backup
Hornetsecurity VM Backup
Score 8.4 out of 10
Medium-sized Companies
Rubrik
Rubrik
Score 8.5 out of 10
Rubrik
Rubrik
Score 8.5 out of 10
Enterprises
Cohesity
Cohesity
Score 8.5 out of 10
Cohesity
Cohesity
Score 8.5 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
HPE Cloud VolumesIBM Data Replication
Likelihood to Recommend
7.5
(2 ratings)
10.0
(1 ratings)
User Testimonials
HPE Cloud VolumesIBM Data Replication
Likelihood to Recommend
Hewlett Packard Enterprise
In our organization, we are using HPE Cloud Volumes for backups storage. HPE Cloud Volumes has given the flexibility of maximum availability and scalability. Now adding space is not a cumbersome process and it can be easily managed by HPE Cloud Volumes as per our need. In another scenario, we have used HPE Cloud Volumes for temporary storing the data for Datacenter move activity. On the downside, I think HPE Cloud Volumes solution is not suitable for temporary need as its more of a long term solution.
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IBM
IBM InfoSphere Data Replication replication allows work on the daily operation and analyzes the replicated data in real-time with no downgrade of performance. This happens thanks to the incremental data load using the log files instead of querying the database for any changes. It serves as an online backup of the database uploading the data to the cloud in real-time.
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Pros
Hewlett Packard Enterprise
  • It Really simplifying our day to day operations for engineers to maintain the backup needs, aligning our infra to actual use
  • You can leverage efficient,and, we have kind of mixed needs for cloud and on-premises storage, It does exceptionally well
  • It really provides a Ransomware Protection and long-term retention.
  • It delivers simple diaster recovery and also its statisfy our backup needs from the edge to cloud for our genesys applications.
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IBM
  • Performance to detect changes using Incremental Data Delivery with logs.
  • Update data in the cloud in real time.
  • Saves data in clusters using Apache Hadoop
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Cons
Hewlett Packard Enterprise
  • Not suitable for small scale enterprises
  • Initial setup is bit difficult
  • Pricing can be more flexible which can suits different customer of different needs.
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IBM
  • Better documentation and examples of Console and API.
  • Integration with machine learning to analyze the data.
  • Examples of how to replicate data from multiple sources and databases to one data lake.
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Alternatives Considered
Hewlett Packard Enterprise
HPE Cloud Volumes Backup unlocks agility and powers innovation. It really eliminate the complexity of day-to-day hassles. For our On-premises and Muticloud backup needs Based on our evaluavtion , we had to come to this decision to go for HPE
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IBM
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Return on Investment
Hewlett Packard Enterprise
  • Backups on HPE Cloud Volumes has significantly reduced the cost of on premise handling of backups
  • It provided storage for datacenter move which reduced the migration time
  • Hosting smaller application in HPE Cloud Volumes has helped in saving operating cost.
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IBM
  • Analize the daily data in real time using data lakes and Machine Learning.
  • Performance of the replication without affecting the relational database of the applications.
  • Use of Apache Hadoop for data clustering improving performance.
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