The Amazon S3 Glacier storage classes are purpose-built for data archiving, providing a low cost archive storage in the cloud. According to AWS, S3 Glacier storage classes provide virtually unlimited scalability and are designed for 99.999999999% (11 nines) of data durability, and they provide fast access to archive data and low cost.
$0
Per GB Per Month
IBM Storage Ceph
Score 8.0 out of 10
N/A
IBM® Storage Ceph® is a software-defined storage platform that consolidates block, file and object storage to help organizations eliminate data silos and deliver a cloud-like experience while retaining the cost benefits and data sovereignty advantages of on-premises IT.
If your organization has a lot of archival data that it needs to be backed up for safekeeping, where it won't be touched except in a dire emergency, Amazon Glacier is perfect. In our case, we had a client that generates many TB of video and photo data at annual events and wanted to retain ALL of it, pre- and post- edit for potential use in a future museum. Using the Snowball device, we were able to move hundreds of TB of existing media data that was previously housed on multiple Thunderbolt drives, external RAIDs, etc, in an organized manner, to Amazon Glacier. Then, we were able to setup CloudBerry Backup on their production computers to continually backup any new media that they generated during their annual events.
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
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.
Since the rest of our infrastructure is in Amazon AWS, coding for sending data to Glacier just makes sense. The others are great as well, for their specific needs and uses, but having *another* third-party software to manage, be billed for, and learn/utilize can be costly in money and time.
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.
We seldom need to access our data in Glacier; this means that it is a fraction of the cost of S3, including the infrequent-access storage class.
Transitioning data to Glacier is managed by AWS. We don't need our engineers to build or maintain log pipelines.
Configuring lifecycle policies for S3 and Glacier is simple; it takes our engineers very little time, and there is little risk of errant configuration.
