When businesses are using RAM as a storage solution, they require a system that will help connect several computers to help them share their memories. The in-memory data grid effectively provides this solution. It connects several RAMs and enables them to work together in parallel.
The system enables the connected computers to process information collectively at a super speed. In-memory data grid is used in situations where businesses need to move or process large volumes of data that might suffer bottleneck limitations when processed from traditional storage. It has several important use cases.
Why are in-memory data grids important?
In memory data grid is important in an environment where technology is developing fast, and businesses are producing large volumes of data. Some of the platforms that contribute to the production of big data are the digital, social, and internet of things capabilities.
They are a catalyst to a business’s exponential growth and they produce large amounts of data daily from millions of transactions and events generated from these systems. Even with such greater volumes of data, businesses require to keep to-notch service delivery to customers and respond in real-time to any customer demands.
Customers are looking for a business system that enables them to sign in fast, place orders, make payments, withdrawals, and follow up on their orders online. On the other hand, businesses need to use every bit of information generated to improve their services and products.
That means the data must be securely stored and accessed fast. This is the point where the in-memory data grid becomes important. By linking several computers and enabling them to work in parallel, businesses improve customer experience and eliminate buffering and bottleneck challenges.
Important use cases of the in-memory data grid
Online banking
Online banking enables customers to do most transactions on their smartphones or computers. They make payments, check balances, transfer funds, make deposits, open accounts, and make inquiries.
Some banks currently have over 5 thousand branches, over 16,000 ATMs, and more than 50 million account holders. The bank systems must remain interconnected and its online system must provide super-fast access. They must keep up-to-date data for all their clients, suppliers, products, and workers.
That means, the amount of data generated daily is huge and cannot be stored or processed on ordinary types of storage. Storing and processing it on such systems would mean using millions of hard disks and complex systems that would require complex engineering technologies.
The banking sector today relies on in-memory data grids to store data and keep its operations smooth. It provides an inexpensive solution backed up by other established architectures.
Trading platforms and trading processing
Trading platforms handle large volumes of data generated every minute. Traders from all corners of the globe connect to the platforms and open accounts, search market trends, make buys, sells, deposits, and withdrawals.
One trading platform could be handling 100 plus million accounts and hundreds of millions of transactions every few minutes. Each action is processed and its history must be stored, user profile, financial status, and every transactional detail.
The data is then aggregated and kept ready to be availed to the client in real-time anytime they need it. Without in-memory data grids, it would be impossible to handle such huge trading metrics.
Large retail stores and e-commerce applications
Huge retail stores handle both online and offline clients. They upload their products online for customers to view and make purchase decisions. On the products, they include reviews, prices, and similar options.
Customers add their choices in carts, make orders, payments, and ask questions. The retailers use the generated data to study customer buying and browsing behavior to help them give better services.
They use online systems to keep updated records of their store stocks, what’s in the process of delivery, stock in shelves, and make new orders. They need to handle large volumes of data and in-memory data grids make this possible.
Advertising and marketing – generating and processing data
Advertisers and marketers rely on data more than any other business sector. They generate data from multiple sources to enable the launch of productive marketing campaigns. They generate data from social media, blogs, search engines, companies’ websites, and other marketing platforms.
They need this information to study customer behavior and understand where to find them, which platforms to invest more and the best ads to create. Each day, marketers and advertisers generate large volumes of data and process complex information to gain insights into the market. They require better storage and data processing techniques that can only be made possible by the use of an in-memory data grid.
Complex social communications on social media platforms
As simple as using the platforms might seem, social media platforms operate under some of the most complex architectures. Some social media platforms have over 2.6 billion monthly users.
Some of the platforms generate as much as 300 petabytes of data which is impossible to store in disks. They store both current and historical data where users can access all communication from the time they opened accounts.
Daily, social media platforms process text messages, images, and videos, and one of the latest technologies they use to store and process large volumes of data is the in-memory data grid.
Online booking and fleet management
Customers cannot wait for pages to buffer and load for five minutes to make a booking. They require super-fast systems that enable them to search, click on a booking company website, and book their trip, hotel, or transfer services.
Booking and transportation businesses also need to manage their fleet through data-driven applications. In-memory computing helps improve data performance from existing applications and eliminates server outages across several remote connections.
It allows the smooth and continuous availability of data across sophisticated booking and fleet management systems.
Conclusion
In-memory data grids help provide effective connection across multiple computers enabling their RAM to process huge data in parallel. It helps store and process data in real-time so that businesses can make informed business decisions.
Some of the areas in-memory data grid is used are open banking, complex trading applications, payment processing, and online commerce. Businesses can process data super-fast and store large volumes of data thanks to IMDG technology.