In-memory computing is the use of random access memory (RAM) in dedicated servers to store vast volumes of data. In-memory computing is faster, efficient, and more reliable in a fast-paced retail business environment that relies on large volumes of data to operate. Using a high-speed analytical appliance (HANA), in-memory computing can process information at speed 10,000 times faster than standard disks. Large retail outlets handling thousands of transactions per minute online require such capacity for efficiency and enhanced delivery of better CX for their customers. Here is how in-memory computing helps the retail industry.
Enhanced performance
Large retail chains running hundreds of conventional outlets and online shops have to process vast amounts of data in their operations. Keeping track of inventory, stock prices, discounts, and accounting rely on sufficient data storage and efficient retrieval at speeds commensurate with operational needs. Whereas standard disk computing can be configured to store data in terabytes and beyond, it has the limitation of retrieval speeds.
Standard hard drive or SSD disks may not handle the high speeds that a retailer processing thousands of transactions per minute online requires. Such transactions can move faster if processed from random access memory, also known as in-memory computing. So, what is in-memory computing? In-memory computing uses cached information stored in RAM, making access a lot faster with the capability to execute millions of read/write operations per second, escalating performance.
By caching information for faster and easy retrieval, a retailer and their online customers can establish price, stock availability, discounts, if any, and check out smoothly at the touch of a few keys. The fast, efficient, and seamless transaction helps to improve customers’ experience and encourages repeat shopping. The increased performance reduces the cost of doing business for the retailer while helping to grow the business and profitability.
Improved reliability
System reliability and stability are critical for any data-driven business to deliver its services efficiently. Business today relies heavily on computing to leverage data in their operations, especially in the digital marketplace. A lot goes into the software development process to ensure that the system integrity is reliable for the support and success of the business.
However, standard disk systems can only stretch that much to cope with high volume traffic and may occasionally crash. This occasional crash from a traffic surge can happen at the worst of times during the holiday shopping season, for instance, and cost a retailer heavily. Couple this with the slower speeds associated with the conventional disk-operated system, and the retailer’s losses can go into millions of dollars.
In-memory computing, with its infinite capacity, has the solution for system reliability that any retailer desires to drive their business. Cached data in RAM is available on-demand and does not suffer from the high traffic fatigue that disk-operated systems have. If something happens and your database goes offline, your point of sale systems will still access data from the in-memory cache without disruption. In-memory computing offers system reliability and continuity, enhancing performance.
Cost-saving
Databases can be and are expensive assets to buy and run for business. The cost of buying and installing a database for a retail business keeps escalating with time and as the needs of the company grows. After the initial purchase, provision has to be made for the cost of maintenance, training, and curation that will keep adding up with time and can affect your bottom line.
For a retailer that requires stability and reliability, it is best to go for proprietary database platforms. These platforms are still expensive, but they offer better after-sale technical support and software maintenance. For those on a shoestring budget, open-source platforms may be the solution, but they come with no support and will eventually cost more in incidental costs. Both options are expensive, scaling up even more costly, and performance may have capacity limitations.
However, in-memory computing can offer a better cost-saving solution when combined with a smaller, affordable database. A retailer can install a smaller but affordable database and augment it with in-memory computing to manage the workload instead of scaling up. A combination of the two systems offers reliability and stability and saves greatly on data costs.
Enhanced scalability
For a fast-growing retailer, sooner rather than later, your database will fail to keep pace with the volume of increased transactions. Databases have a limitation on throughput, and when exceeded, they slow down considerably. The online shopper does not have the luxury of time to wait for their request to be processed in minutes rather than seconds.
Holiday seasons are the worst time for retailers with smaller databases as they will suffer many cases of dropped online transaction requests. With the increased traffic, the database may hang altogether and ruin your business and reputation as customers abandon your site. Faced with such a scenario, you need a database that you can easily and affordably scale up to keep the business running.
In-memory computing can provide the scalability you need to boost the performance of your database at a fraction of the cost. A simple addition of a flexible in-memory cache with adjustable cluster sizes will accelerate your database performance. Conversely, in-memory data stores are also scalable for increased traffic by simple partitioning and replication.
Simple application
In-memory computing in the retail application provides customers with simple use patterns that enhance their experience on the platform. Data can be queried by key or range-based for a broader inquiry according to the needs of the user. This is easily achievable because in-memory data stores can support a complex and larger variety of data structures to serve any request.
In-memory data solutions combine complex structures and easy access patterns that the traditional database lacks. Storage of multiple data structures is straightforward with simplified coding to attain better results without the need to convert or serialize. In-memory also provides a superior database management function that automatically deletes old data through automatic eviction to avoid clutter.
In-memory computing provides retailers with better options for backups, failover, and capacity management. The retailer can write and maintain less code to cover all transactions efficiently.