Most organizations have multiple types of data to store. Data size, access speed, and application priority dictate the type of storage that different data needs. Therefore, many organizations use several different types of storage in the data center rather than one homogeneous type of storage.

The two main forms of data center storage are storage area network (SAN) and network attached storage (NAS). A SAN uses a network hardware fabric and switches to connect servers to storage. SANs are suitable for block I/O and structured data, such as relational databases. SANs require Fiber Channel or Ethernet networking, such as iSCSI. NAS, on the other hand, accesses files with a protocol and is optimal for remote file serving. The NAS operates as a server with its own file server and provides centralized data management. This is better for unstructured data.

Hybrid Storage Arrays

Hybrid storage arrays combine different types of storage, mixing flash memory, hard disk drives (HDDs), tape, and object-based and cloud storage into a single storage infrastructure. Data types, such as live data, file server data, streaming data, and virtual systems, often have different storage requirements. A hybrid storage array can bring the speed and low latency of flash to the table while providing the flexibility and lower costs of hard drives, tape, and cloud. However, hybrid storage is more complex than an all-flash or all-hard drive system.

A hybrid storage array typically requires tiering software. This software helps organize data into different tiers in the storage system based on factors such as activity, throughput requirements, and redundancy and, therefore, helps determine where specific data resides in the system.

Storage Virtualization

The storage virtualization process can help companies accommodate multiple types of storage arrays and better predict storage costs. Many sellers offer software management tools that can help with storage virtualization, including Flexify.IO, Nutanix AOS, StarWind Virtual SAN, and DataCore SANsymphony.

Different storage virtualization tools can virtualize hardware storage arrays, create virtualized storage on hyperconverged infrastructure, or specialize in cloud-native storage. Additionally, some tools support different types of storage; some tools only work with block storage, and others work at the file level. Consider the type of storage, availability, and use of the management tool.

When considering different virtual disks, especially VMware, choose from raw, thin, and thick disks. A raw disk connects a storage LUN directly to a virtual machine within a SAN. A raw disk stores a virtual machine’s disk data in a small disk descriptor file on that virtual machine’s working directory and improves application I/O performance. A thick disk, on the other hand, can improve performance and security by using thick provisioning to pre-allocate physical storage. Finally, a lightweight disk maximizes disk efficiency by consuming only the amount of disk space it needs to operate.

Data lake vs data warehouse, cloud vs on premise

A data lake is a large repository for storing raw data in its native format. Compared to a traditional data warehouse, which stores data in hierarchical levels, a data lake stores data as files or objects in a flat architecture.

Data lakes and data warehouses requires a lot of storage, especially for a large organization. Many storage vendors offer specialized products for each storage architecture. For example, Dell EMC’s Elastic Data Platform and Hitachi Vantara are suitable for large-scale on-premises data lake deployments. Vendors like IBM, NetApp, and HPE have offerings that can work with either style of architecture. Meanwhile, cloud providers such as AWS, Microsoft, and Google Cloud Platform offer storage as a service in either architecture.

Container storage

Due to the inherent agility of containers, application developers working with them need persistent storage for the containers they deploy.

Containers change data center storage needs in different ways.

Container architectures require three types of storage: image storage, a data store for container management, and container application storage. Data centers can store images and container management data with existing shared storage architectures. Container application storage, however, requires a specific system data volume – or persistent volume – in the container’s namespace to give the container direct read or write access to a directory or file share. of the host system.