IBM Storage Ceph vs. StorPool

Large scale data storage: Red Hat Ceph Storage is designed to be highly scalable and can handle large amounts of data. It's well suited for organizations that need to store and manage large amounts of data, such as backups, images, videos, and other types of multimedia content.Cloud-based deployments: Red Hat Ceph Storage can provide object storage services for cloud-based applications such as SaaS and PaaS offerings. It is well suited for organizations that are looking to build their own cloud storage infrastructure or to use it as a storage backend for their cloud-based applications.High-performance computing: Red Hat Ceph Storage can be used to provide storage for high-performance computing (HPC) applications, such as scientific simulations and other types of compute-intensive workloads. It's well suited for organizations that need to store

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Storpool performs well on block level (and that is what we use it for). It is not yet supporting a kind of distributed filesystem or object storage - a filesystem layer needs to be built on top of it.

• Highly resilient, almost every time we attempted to destroy the cluster it was able to recover from a failure. It struggled to when the nodes where down to about 30%(3 replicas on 10 nodes)
• The cache tiering feature of Ceph is especially nice. We attached solid state disks and assigned them as the cache tier. Our sio benchmarks beat the our Netapp when we benchmarked it years ago (no traffic, clean disks) by a very wide margin.
• Ceph effectively allows the admin to control the entire stack from top to bottom instead of being tied to any one storage vendor. The cluster can be decentralized and replicated across data centers if necessary although we didn't try that feature ourselves, it gave us some ideas for a disaster recovery solution. We really liked the idea that since we control the hardware and the software, we have infinite upgradability with off the shelf parts which is exactly what it was built for.

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• Distributed Storage array with very high throughput in terms of reading & write operations.
• Horizontal scaling without much complexity of management.
• Easily integrate with OpenStack cloud.
• Doesn't depend on proprietary hardware, integrates with commodity hardware.

• GUI based mainetenence should be developed
• Unable to detect storage latencies
• VM to disk mapping should be visible so as to save some critical applications data in case of HDD failures

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• Graphical interface is for monitoring and stats, but not for operations.

MongoDB offers better search ability compared to Red Hat Ceph Storage but it’s more optimized for large number of object while Red Hat Ceph Storage is preferred if you need to store binary data or large individual objects. To get acceptable search functionality you really need to compile Red Hat Ceph Storage with another database where the search metadata related to Red Hat Ceph Storage objects are stored.

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We made a very careful selection of our storage vendor and solution. After researching the newest technologies, our team decided to deploy a software-defined storage solution from StorPool.

• Ceph allows my customer to scale out very fast.
• Ceph allows distributing storage objects through multiple server rooms.
• Ceph is fault-taulerant, meaning the customer can lose a server room and would still be able to access the storage.

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• We have not calculated precise ROI. We focused on getting the best solution at a reasonable price, based on market research. Initially, we didn’t need a lot of capacity, so we invested in servers and network, which could handle several times more capacity, but bought smaller drives to keep the investment low. We achieved a starting price of $3.2/GB usable and $1.4/GB logical. Later we expanded the capacity by adding more drives to the system. Currently, the system has a price of approximately $2.3/GB usable and $0.99/GB logical and a price of $0.09/IOPS.