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Top 5 Storage Trends in the Era of Big Data and IoT

Digitalization, Big Data and Internet of Things (IoT) are currently force companies to fundamentally renew or consolidate their IT landscape. In contrast to conventional homogeneous storage environments, the future storage concepts need to meet the increasing demand for scalability and flexibility.

The storage landscape is currently undergoing rapid change. Conventional storage technologies such as direct-attached storage (DAS), Network Attached Storage (NAS) or Storage Area Networks (SAN) have had their data center. These changes in the data center, IT managers need to adjust now.

Due to the increasing need for digitalization, companies often have to process many different data in a very short time. As the digital transformation reaches almost every business area, the demands on the performance and agility of IT are constantly increasing. Innovative IT concepts are therefore essential to develop new data-centric business models.

Cloud storage brings cost advantages

Cloud storage represents an interesting alternative to on-premise storage from an economic and technical point of view. Because gateways offer a simple connection between the internal infrastructure and the Cloud, there are a wide range of deployment scenarios in which public Cloud storage companies can create new scalability, maintenance, and disaster recovery concepts.

Full-Flash for highest storage performance

In the case of transaction-intensive applications such as complex databases, data analysis in real-time or social networks, hard disk-based systems quickly reach their limits. Predestined for such tasks are so-called full-flash or all-flash arrays, which are exclusively equipped with flash memories, have high I/Os and low latencies. The advances in Flash technology enable increased capacities at a lower cost, thereby contributing to the success and attractiveness of these systems on the storage market.

Hybrid storage combines capacity and performance

If performance and at the same time high capacities are the focus, hybrid storage systems play their strengths. They combine the capacity of hard disks with the performance of flash memories that act as intelligent caches in these systems. For example, in order to cover the short-term load peaks during a bootstorm, flash performance is available; while in the standard operation, the performance of classical hard disks in combination with intelligent caching and writing algorithms is completely sufficient.

Server-based storage – scalable and virtualized

Server-based storage is usable in two independent scenarios: if it is part of a hypervisor, one speaks of a hyperconvergent system; for anyone who wants to build an integrated, easy to orchestrate virtual infrastructure as a private Cloud, such a system is the first choice. In the second application, server-based storage is the basis for many software-defined storage solutions that provide storage services to standard hardware, enabling virtually any horizontal scale (scale-out) of server-based storage.

Storage tiering takes advantage of all storage media

If different storage requirements are to be served at the same time, storage tiering systems are suitable. The data is stored here on different storage media depending on the access frequency. Frequently the needed data is on the fastest storage medium, rarely needed on the slowest. The distribution of the data is handled by an intelligent management solution, which monitors the access behaviour. If existing systems are to be integrated into a new storage design, the use of storage tiering is a software-defined storage concept.

Which storage solution is the right one?

Whether public Cloud, hybrid Cloud or private Cloud, whether on-premise or off-premise, the way how an application should process data determines which storage architecture is used. There is no flat-rate solution.

If, however, large amounts of unstructured data are required to be processed in real-time, solutions based on the All-Flash architecture are a good choice. They can process Data Mountains quickly and with low latency, making them ideal for such data analytics applications. On the other hand, a hybrid Cloud system is preferred to cover short-term load peaks. For static data processing, such as backups, a public Cloud architecture is well suited.

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