Use Cases



Accelerate online and offline applications

Business applications are usually subject to SLAs. Whether it’s driven by business requirements, customer expectations or regulation, offline and online applications need to meet various performance standards. But when the application is dealing with a large amount of data, combined with intensive compute, latency may increase and performance may not meet the SLA. This gets even worse when the data is stored in a legacy database that is not designed for high performance.

Adding a caching layer between the database and the application will increase performance significantly, accelerating your applications without the need to replace your database.


In many industries, regulation requires disclosure or reporting within a certain time frame. For example, financial services are usually required to report daily post trade reconciliation. And car manufacturers in some markets are required to calculate CO2 emissions in real-time and disclose it with any car quote. Failing to meet these regulatory requirements may have severe implications, such as hefty fines. Using in-memory cache to speed up your applications will ensure you meet the requirements and avoid fines and other negative consequences.

Power your digital applications with an in-memory cache or digital integration hub to offer a better customer and internal user experience. Data can be accessed with a millisecond latency even with high concurrency of users or transactions.

During peak loads your applications are required to handle multiple times the normal load. Sometimes you can plan for it in advance, such as end of year calculations or black Friday shopping spree, and sometimes they come unannounced, such as brexit. Legacy databases can’t usually scale dynamically, which means you need to choose between over-provisioning of expensive infrastructure that will sit idle most of the year, or provisioning for the normal load and facing bottlenecks and performance degradation when peaks happen.  

With a distributed in-memory data store you don’t need to choose. Scale up or out to handle peaks, scale down or in when it’s back to normal.

Boosting your applications with an in-memory caching layer can give you better insights faster. Your models can use more data, thus delivering faster and more accurate results. Whether it’s calculating real-time market risk for trading, forecasting revenue, or planning supply chain, the faster you get the results, the better your business decisions are. 

Case Studies

Avanza Delivers Digital Banking Services with Millisecond Response; Growing Customer Base by 5X

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PriceRunner Case Study

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A Leading Airline Accelerates Forecasting Process by 22X

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