Technical Papers for Developers

Download datasheets, white papers, application notes, industry briefs, reports, and eBooks from GridGain® Systems on a range of topics related to in-memory computing. These free resources discuss the technology behind GridGain and Apache® Ignite and discuss common and emerging use cases for in-memory computing. Leaders in the in-memory computing field write about the current state of in-memory computing technology as well as common and emerging use cases.

All GridGain literature is available for free download.

Case Study
Intelligentpipe Leverages GridGain® In-Memory Computing Platform for Real-Time Analytics Big Data Software Company Leverages GridGain for Terabytes of Mobile User Traffic Data With offices in Finland and Singapore, Intelligentpipe is a b
Report or Guide
By reducing the latency in operational and analytical processing, organizations can
White Paper
Capital markets applications often require high performance, massive scalability, and high-performance data access across the enterprise to meet the demands of modern, digital business activities.
eBooks
This eBook, Part 1 in the In-Memory Computing for Financial Services eBook Series, discusses how financial service firms are using in-memory computing platforms such as GridGain and Apache® Ignite™ to address the challenges of high-frequency trading, fraud prevention and real-time regulatory compliance.
White Paper
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.
Application Notes
FinTech companies face many of the same challenges as their largest customers. Their new channels and services, as well as core banking, insurance, and real estate systems, must deliver 100-1000x speed and scale compared to existing systems. Download this Industry Brief and learn how the GridGain In-Memory Computing Platform can address these issues and more.
Product Comparison
This in-depth feature comparison shows how the most current versions of GridGain Professional Edition, Enterprise Edition, Ultimate Edition and Redis Enterprise (and their respective open source projects where relevant) compare in 25 categories.
White Paper
This white paper discusses how to increase and accelerate your Oracle database speed and scale using in-memory computing. There are many Oracle® options for adding speed and scale to Oracle Database, or for replacing it—including Oracle RAC, Oracle Database In-Memory, Oracle Exadata, Oracle GoldenGate, Oracle TimesTen Classic, Oracle TimesTen Scaleout, and Oracle Coherence—and…
Case Study
FSB deployed GridGain to speed up its Postgres database and scale-out their cluster. For FSB Technology to support live betting during sporting events, their betting platform must be real-time and highly performant. Huge amounts of event data must be constantly updated, and immediately available to a vast number of clients. GridGain Enterprise Edition helped FSB add nodes in…
White Paper
This white paper covers the architecture, key capabilities, and features of GridGain®, as well as its key integrations for leading RDBMSs, Apache Spark™, Apache Cassandra™, MongoDB® and Apache Hadoop™. It describes how GridGain adds speed and unlimited horizontal scalability to existing or new OLTP or OLAP applications, HTAP applications, streaming analytics, and continuous…
Application Notes
Leading banks and fintech companies have already adopted the GridGain in-memory computing platform as the foundation for FRTB and their next generation trading systems. With GridGain, these banks have been able to rapidly implement the required XVA calculations, continuously run their new risk models and price new securities in near real-time. Learn more now.
eBooks
This Machine Learning and Deep Learning primer, the second in the “Using In-Memory Computing for Continuous Machine and Deep Learning” Series, is a hands-on tutorial that covers how to use the Apache Ignite built-in machine learning algorithms Linear Regression, k-Nearest Neighbor (k-NN), k-Means Clustering, and Compute Mean Entropy.
White Paper
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.
Case Study
Expertcity uses GridGain in-memory computing solutions to power its platform that allows over 650 lifestyle and consumer brands to connect with key brand advocates to help them improve sales in their retail channels. Experticity uses GridGain so that its architecture scales with company growth, analyzes the data quickly enough to send users to the next logical step in the…
Report or Guide
While IT shops may be generally familiar with traditional in-memory databases - an
eBooks
This eBook, Part 2 in the In-Memory Computing for Financial Services eBook Series, discusses how financial service firms are using in-memory computing platforms such as GridGain and Apache® Ignite™ in their strategy to improve the performance of payment systems, IoT applications, and bitcoin/blockchain technology.
White Paper
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