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


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 in-depth the architecture, key capabilities and features of GridGain®, and as well as its key integrations such as leading RDBMSs, Apache Spark™, Apache Cassandra™, MongoDB® and Apache Hadoop™. You will learn how GridGain can add in-memory speed and unlimited horizontal scalability to your company’s existing or new OLTP or OLAP applications;…
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This paper, written by GridGain founder and CTO, Nikita Ivanov, sums up the architecture and key capabilities of the Apache® Ignite™ project. It discusses the key features of Apache Ignite and integrations with Apache Spark and Apache Cassandra.


Optimizing your customer’s digital experience requires speed, scale, real-time intelligence, and automation. Companies have succeeded with their digital transformations by adopting an in-memory computing (IMC) strategy. In this eBook, you’ll learn about best practices for establishing a sound and cost-effective in-memory computing foundation for digital…
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This Machine and Deep Learning Primer, the first eBook in the “Using In-Memory Computing for Continuous Machine and Deep Learning” Series, is designed to give developers a basic understanding of machine and deep learning concepts. Topics covered include:
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Application Notes

Over the last few years, new business demands – from digital transformation to improving the customer experience – have overwhelmed existing SQL infrastructure. The increase in interactions through new Web and mobile apps and their underlying APIs are creating massive volumes of queries and transactions that are overloading existing databases. Improving the customer…
GridGain and Ignite provide the ideal underlying in-memory data management technology for Apache Spark because of its in-memory support for both stored “data at rest” and streaming “data in motion.” Learn how this makes many Spark tasks simple, including stream ingestion, data preparation and storage, stream processing, state management, streaming analytics, and…

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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