Before data storage became so affordable, the cost was one of the most important factors in determining what data to store. As storage costs decreased, data volumes increased. Companies needed to consider technology, architecture and processes in order to gather, process and retain data.
Organizations had to look at various factors when considering storage, such as its intended use, its relevancy and its analytical purpose. For short-term needs, computers rely on random access memory (RAM) but if they need to retain and save bigger records, they need long-term memory storage and this is what different types of data storage solutions can provide.
Memory and storage
Memory and storage can be confused because, in the past, these terms were often used interchangeably. Memory is often thought of as short term, whereas data storage is thought of as long term. Storage is the mechanism that enables a computer to retain data, either temporarily or on a permanent basis. There are two main types of storage – volatile and non-volatile.
Short-term memory stores data temporarily and holds on to it only while the computer is on. It is volatile memory as the data isn’t accessible over the long term. Random Access Memory (RAM) is an example of short-term memory. Every time the operating system starts or a program launches, the relevant code and/or data is loaded into RAM. The measurement of RAM is in Megabytes or Gigabytes and users may add extra RAM to their computers to speed up its performance.
The data in long-term memory is stored permanently and doesn’t disappear when the computer is turned off. It is permanent and non-volatile.
Volatile storage tends to be much faster than non-volatile storage due to its proximity to the process, but it is also comparably smaller. Secondary storage can hold larger data sets and keep them inactive until they are needed again.
Data storage is a central component of Big Data and modern architectures don’t just consist of RAM and disks. They often have layers upon layers of increasing memory size, with only the topmost layer being non-volatile.
The operational data store (ODS) was developed as a central store for information from different data silos. An Operational Data Store contains the most up-to-date information from various transactional systems to enable better business reporting. It constantly overwrites data to offer the most recent, relevant snapshot for reporting. Offering current and integrated operational data can greatly improve business efficiency because simple queries can be performed on small data sets. This offers a more holistic perspective than relying on reports from individual data sources.
Types of data storage
From personal data storage devices to the data center and cloud-based data repositories, organizations now have many options to store and organize their data. There are two broad types of data storage: Direct-attached storage and network-attached storage. Many devices fit into each of these categories and each has advantages and disadvantages.
Direct-attached storage
Direct-attached storage stands for all types of physical data storage devices directly connected to a computer. This may be a hard disk drive which is usually internal but it can be external to expand the disk size.
The first hard disk drive (HDD) was introduced by IBM in 1956 and was the size of a refrigerator. IBM also released the first floppy disks and by the mid-70s, they became the most widely used form of portable storage. In the 1980s, hard disk drives became compact disks, and solid state drives (SSDs) replaced spinning disks with solid chips and flash memory. Flash drives appeared in 2000. They are small, very portable storage devices that plug into computers with a built-in USB plug.
DAS is still the standard solution for keeping small-scale records and data backups or for transferring data between devices. It can be more affordable than NAS solutions but can make sharing data between machines more cumbersome.
Network-attached storage (NAS)
Network-attached storage is a hardware unit that features file-level architecture and more than one computer in a network can access data as long as all users are connected to the internal network. This is better for collaboration and sharing of data. A NAS unit may feature various storage disks or hard drives, lightweight operating systems, processors, and RAM.
A Storage Area Network (SAN) helps to assemble complex on-premises data management architecture. There’s a dedicated network for data exchanges and a data storage system that consists of on-premises hardware. Its purpose is to act like a “highway” that allows for the transmission of data between servers and storage devices throughout an organization.
The latest innovations in network storage can provide comprehensive solutions for organizations that need to store large volumes of sensitive information. For example, software-defined storage (SDS) decouples the software layer between where data is stored physically and how it is retrieved.
Cloud storage
Rather than storing files on-premise or on storage networks, it has become possible to store data in the cloud as a cost-effective and scalable alternative. Data storage happens in an off-site location accessed through a public or private network connection. The provider hosts, manages, secures and maintains the servers and the infrastructure offering access to the data whenever it is required.
Many new business ideas have become possible thanks to the potential of cloud storage. Low-cost, always-on resources enable business leaders to concentrate on their main goals rather than on day-to-day operations.
Hybrid cloud storage is also possible and organizations can decide whether they want to store data in the public or private cloud. Highly regulated data may be stored in a private cloud and less sensitive data in the public cloud. The cloud may also be used to back up information stored on-premise so it’s available in the event of a problem on-premise.
Conclusion
Storage capabilities have greatly increased over the past few decades and modern hard drives can hold several terabytes of data. As data keeps growing, more ways to store it are likely to evolve. Some of the most important factors to consider are security, reliability and the cost to implement and maintain the infrastructure. Companies with a balanced storage infrastructure can use the right technology for different storage needs.
Hey, nice article about short term vs long term data storage. Keep on adding this type of valuable content. Hope to read more from you. Thank you.