Use Cases

API SCALING

About

Future-proof business growth and support seasonal fluctuation with no need for up-front investment

Many businesses today face incidental and seasonal peak times. Enterprises that run on unscalable systems with a limited cap of transactions per second may end up denying service from potential buyers. Trying to prevent this with upfront over-provisioning typically spikes CAPEX costs

In addition, business applications are usually subject to SLAs, whether driven by business requirements, customer expectations or regulation. When faced with large amount of data, combined with intensive compute, latency may increase and performance may fail short in meeting the target SLA.

This gets even worse when the data is stored in a legacy database that was never designed to support high-performance applications. Moreover, APIs created over legacy systems are often not scalable, due to the scaling limitations of the underlying systems. Overcoming these issues typically requires up-front investment in costly hardware and high overhead.

The GigaSpaces Smart DIH is designed to address these challenges:

APIs are built over a scalable data platform; scaling up and out, and only when required
Consolidating replicated data into a single system simplifies scaling operations by abstracting any scalability variations in the originting systems of record

Smart DIH decouples applications from diverse and disparate SoRs

and replicates operational data into a low-latency, high-performance layer that continuously supplies digital applications with fresh data in real-time.

Smart DIH’s no-code tools empower data professionals to launch new services without having to rely on programming expertise. As a result, organizations can scale APIs in response to business needs and rapidly deliver new digital services while ensuring high throughput, low latency, and always-on service availability.

Benefits

Meet regulatory requirements

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.

Deliver great digital application customer experience

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.

Handle peak loads without impacting performance and without over-provisioning expensive resources

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.

Make informed business decisions based on faster more accurate analytics

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.

Learn how InsightEdge is being used by Financial and Insurance Services to become insight driven.

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