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.

Datasheets

This data sheet provides the key features and benefits of the GridGain in-memory computing platform.
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If your company is one of the tens of thousands of organizations that use Apache® IgniteTM or GridGain® Community Edition in a production environment, GridGain Basic Support can provide you with peace of mind that you have a trusted partner to help keep your environment running flawlessly. The service includes....
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White Papers

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…
This white paper discusses the architecture, key capabilities and features of the Apache® Ignite™ in-memory computing platform project. Learn how it adds speed and scalability to existing and new applications.

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.
In this eBook, you’ll learn best practices for establishing a sound and cost-effective in-memory computing foundation for digital transformation. This eBook is Part 1 of the best practices for digital transformation series.

Application Notes

Download this Application Note and learn how GridGain fosters digital transformation and improves the customer experience by adding speed, scalability, and in-memory computing to SQL architectures overwhelmed by the huge increase in data and the need to implement new business demands.
GridGain and Ignite provide an ideal underlying in-memory data management technology for Apache Spark because it supports both in-memory “data at rest” and “data in motion.” Learn how this simplifies many Spark tasks like stream ingestion, data preparation and storage, stream processing, state management, streaming analytics, and machine and deep learning.

Reports and Guides

451 Research believes that an increasing proportion of enterprise operational applications will rely on hybrid operational and analytic processing (HOAP) to support use cases such as recommendations, personalized content and offers, and real-time fraud analysis. The availability of high-performance in-memory computing technology, therefore, lays the foundation for…
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While IT shops may be generally familiar with traditional in-memory databases - an
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