GridGain is a Cost Effective Solution for Delivering Business Value to the Digital Enterprise

GridGain provides in-memory speed and massive scalability to new or existing applications which can provide the performance needed for digital transformation and omnichannel customer experience initiatives. Built on the open source Apache Ignite project, GridGain is a cost effective solution for accelerating and scaling your existing applications which is used by GridGain customers across a wide variety of use cases and industries.

The GridGain in-memory computing platform easily integrates with your existing applications, deployed as an in-memory computing layer between the application and data layer of your new or existing applications. GridGain is typically deployed as an in-memory data grid for existing applications and as either an in-memory data grid or as an in-memory database for new applications. A Unified API, including ANSI-99 SQL and ACID transaction support, provides easy integration with your existing applications, enabling your organization to create modern, flexible applications built on an in-memory computing platform which will grow with your business needs.

A variety of resources including white papers, webinar recordings, application notes, product comparisons, and videos are listed below which discuss use case considerations from a business benefits standpoint.

Resources

This white paper will discuss the challenges facing today’s insurance industry, the opportunities new technologies can offer, and the crucial edge that providers can gain with solutions such as the GridGain in-memory computing platform.
This white paper discusses how an in-memory computing platform solution like GridGain gives financial services companies the speed, scalability, and flexibility they need to build successful IoT-based applications and services.

The shift to digital payments is taking place in many forms: bitcoins, mobile wallets, “tap and go” payment transactions, peer-to-peer money-transfer apps and more. Worldwide, the mobile payments market alone has grown from $235 billion in 2013 to a projected value of almost $800 billion in 2017 and over a trillion dollars by 2019.

This white paper will give you a better understanding of how in-memory computing forms the backbone of successful high performance, highly scalable and mission-critical technology solutions in the FinTech industry. You will also learn how in-memory computing helps address many current limitations of legacy financial systems.

Businesses have a long wish list for their software solutions. They want stability, reliability, security, scalability, and speed. They can get there today with serverless architectures that rely heavily on virtualization and containerization, distributed systems, and microservice-based architectures.

To achieve competitive application performance, scalability, and analytical sophistication, many financial-services providers are turning to in-memory computing solutions. This white paper will discuss the increased expectations of investors, the new challenges providers are facing, and how providers can gain the edge they need with solutions such as the GridGain in-memory computing platform.
One way to evolve eCommerce technology is to make it as fast, available, and scalable as possible. This white paper discusses how an in-memory computing platform can accomplish this, while both providing competitive advantage and addressing the issues that eCommerce developers face.

Bitcoin and blockchain, the digital-ledger technology behind this electronic currency, are generating enormous amounts of interest in the financial services industry. Most of the larger banks are investigating this area, and many technology companies are building platforms to enable blockchain technology for financial services firms.

Spread betting offers some compelling advantages, including low entry and transaction costs, preferential tax treatment, and a diverse array of products and options. Traders can bet on any type of event for which there is a measurable outcome that might go in either of two directions – for example, housing prices, the value of a stock-market index, or the difference in the scores of two teams in a sporting event.

Financial fraud detection and prevention is not a simple task, and firms must tackle it simultaneously with other crucial tasks such as ensuring regulatory compliance. To accomplish these data-intensive tasks in a timely manner, financial firms need solutions that are flexible, scalable, reliable, and fast enough to analyze extremely large datasets in real-time.

Digital transformations are arguably the most important initiatives for companies. They can literally make or break a business.  But transformation is not easy because there’s a big digital divide between the speed, scale and computing needed for new digital channels and APIs, and what existing systems can deliver. Learn how leading digital innovators have solved these problems by using in-memory computing, and the roadmaps that worked for them.

GridGain Cloud, which enables companies to create an in-memory SQL and key-value database in minutes, is now in Beta. Learn from the experts how to use GridGain Cloud, and get up and running. This 60-minute hands-on session will:

It's hard to improve the customer experience when your existing applications can't handle the ever-increasing customer loads, are inflexible to change and don't support the real-time analytics or machine learning needed to improve the experience at each step of the way. Join us for part 1 of the in-memory computing best practices series. Learn how companies are not only adding speed and scale without ripping out, rewriting or replacing their existing applications and databases, but also how they're setting themselves up for future projects to improve the customer experience.

The need to engage more intelligently in real-time during each transaction or interaction, whether it's to add personalization and recommend products or to help improve the overall customer experience across multiple channels, is driving the need for new infrastructure with much lower latency and much higher scalability. The solution that many companies have adopted is to move all the transactional and analytic data, and to collocate computing together in memory using In-Memory Computing technologies.

Ever-changing financial regulatory compliance policy is causing unprecedented and growing technical challenges. Banks and other financial institutions must continuously monitor, collect, and analyze vast amounts of data from multiple, disparate sources in real-time. Coping with these challenges in an efficient way requires not only an extremely fast, scalable, and cost-effective data technology, but also one that can incorporate and handle new requirements as they arise.

Data is critical to the success of financial services companies. Market data, customer data, trade data, and compliance data are retained, processed and analyzed to help firms not only stay afloat but also ahead of the competition. During this webinar, we will discuss the different types of financial data, ways financial and fintech companies process it, and show how in-memory computing is used to instantaneously analyze and make decisions based on internally and externally available data.  We will discuss:

The Insurance industry is undergoing significant changes.  In addition to economic and political uncertainty, insurers face investment income pressure from low interest rates. Coupled with this are the challenges of social and regulatory changes based on new customer expectations and government and employer policies.

The payments industry is being disrupted.  Mobile payments, instantaneous payments and embedded payments are changing the way consumers interact with their financial institutions.  The current payments paradigm requires financial services and fintech companies to upgrade their digital infrastructure to support processing transactions in a low-latency, scalable and secure manner. 

If your eCommerce initiatives are struggling to keep up with customer demand, then in-memory computing may be the solution you need to take performance and scale to the next level. Yesterday’s application and data architectures cannot achieve the speed and scale offered by in-memory computing. In addition, in-memory computing is more efficient than disk-based systems and can frequently be used to drive infrastructure consolidation projects and decrease costs.  

Technology is changing traditional retail banking business models. Online banking and mobile banking are generating significantly more transactions than live teller-based banking.  This increase in automation is challenging banks to redesign their legacy systems to accommodate the increased quantity and complexity of transactions and analytics. Such changes require a fast, scalable, distributed and secure architecture. 

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