There are some drawbacks in HPE Ezmeral Data Fabric when it comes to the interoperability part. HPE Ezmeral Data Fabric is not compatible with third-party tools. For example, HPE Ezmeral Data Fabric is not compatible with Informatica and one other tool, but considering my company's use cases, we tried but failed with the integration part. The aforementioned areas can be considered for improvement in the solution.
Regional Head of Data and Application Platform at a financial services firm with 10,001+ employees
Real User
Jan 18, 2023
Upgrading Ezmeral to a new version is a pain. They're trying to make the solution more container-friendly, so I think they're going in the right direction. The only problem we've had in the past was the upgrades. The process isn't smooth due to how the Red Hat operating system upgrades currently work. They're transforming their host stack to increase cloud readiness and edge compute capability. HPE is transitioning from a standard data-driven approach to one powered by AI analytics. That's something they have released very recently. I haven't tried that, but it will probably make things easier. The ability to adapt Ezmeral to the public cloud is probably missing. I've heard that they're getting leaner. However, it doesn't have a clear managed services offering for you if you want to deploy this stack on the cloud. That's a problem. This probably won't meet your needs if you require consistency across on-prem and the cloud. It's not Ezmeral's fault. None of the products would fit the bill. Cloud offerings are biased towards their own implementation. It's a general issue on most big data platforms. They're already working towards that, but it hasn't been released.
The interface part, what I'm calling the integration part, could be improved. Although it was able to connect to Hadoop, pocket files and so on. For example, providing some API endpoints for capturing all the streaming parts wasn't well-developed at that point. But today, if I'm honest, they've added all these streaming ports. Having the ability to extend the services provided by the platform to an API and micro-services architecture, could be very helpful. It could be used in different contexts and also integrated into a personal system for example or mobile applications, mobile content or some sort, and so on. API and micro-services architecture, all the features behind that, could be very interesting.
HPE Data Fabric delivers robust data management with features like multi-tenancy, security, and ease of configuration. It supports high performance and unified analytics, making it a reliable choice for organizations looking to manage extensive data efficiently.HPE Data Fabric provides a comprehensive data management platform with clustered node distribution and no single point of failure, ensuring high availability. Its compatibility with MapR-DB and NFS functionality allows integration with...
There are some drawbacks in HPE Ezmeral Data Fabric when it comes to the interoperability part. HPE Ezmeral Data Fabric is not compatible with third-party tools. For example, HPE Ezmeral Data Fabric is not compatible with Informatica and one other tool, but considering my company's use cases, we tried but failed with the integration part. The aforementioned areas can be considered for improvement in the solution.
The product is not user-friendly.
Upgrading Ezmeral to a new version is a pain. They're trying to make the solution more container-friendly, so I think they're going in the right direction. The only problem we've had in the past was the upgrades. The process isn't smooth due to how the Red Hat operating system upgrades currently work. They're transforming their host stack to increase cloud readiness and edge compute capability. HPE is transitioning from a standard data-driven approach to one powered by AI analytics. That's something they have released very recently. I haven't tried that, but it will probably make things easier. The ability to adapt Ezmeral to the public cloud is probably missing. I've heard that they're getting leaner. However, it doesn't have a clear managed services offering for you if you want to deploy this stack on the cloud. That's a problem. This probably won't meet your needs if you require consistency across on-prem and the cloud. It's not Ezmeral's fault. None of the products would fit the bill. Cloud offerings are biased towards their own implementation. It's a general issue on most big data platforms. They're already working towards that, but it hasn't been released.
The deployment could be faster. I want more support for the data lake in the next release.
The interface part, what I'm calling the integration part, could be improved. Although it was able to connect to Hadoop, pocket files and so on. For example, providing some API endpoints for capturing all the streaming parts wasn't well-developed at that point. But today, if I'm honest, they've added all these streaming ports. Having the ability to extend the services provided by the platform to an API and micro-services architecture, could be very helpful. It could be used in different contexts and also integrated into a personal system for example or mobile applications, mobile content or some sort, and so on. API and micro-services architecture, all the features behind that, could be very interesting.