GridGain White Papers, Application Notes and Datasheets

Downloadable Files on In-Memory Computing Topics

Download datasheets, white papers 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 also about common and emerging use cases.

Datasheets

This data sheet provides the key features and benefits of the GridGain in-memory computing platform.
This data sheet provides the key features and benefits of the GridGain In-Memory Accelerator for Hadoop and Spark.

White Papers

Platform
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; new or existing HTAP applications; streaming analytics; and continuous learning use cases involving machine or deep learning.
Platform
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.
Platform
This white paper reviews why IMC makes sense for today’s fast-data and big-data applications, dispels common myths about IMC, and clarifies the distinctions among IMC product categories to make the process of choosing the right IMC solution for a specific use case much easier.
Platform
This white paper provides an overview of in-memory computing technology with a focus on in-memory data grids. It discusses the advantages and uses of an IMDG and its role in digital transformation and improving the customer experience. It also introduces the GridGain® in-memory computing platform, and explains GridGain’s IMDG and other capabilities that have helped companies add speed and scalability to their existing applications.
Platform
The in-memory computing solutions of the future must not only offer the key capabilities that database users expect, such as SQL support, but also provide a bridge to emerging use cases, such as machine learning and deep learning, and transformative new storage technologies, such as non-volatile memory. This white paper delves into these application-crucial topics and then shows how Apache Ignite and GridGain are addressing them.
Use Cases
Many companies who have succeeded with IoT have solved their challenges around speed, scalability and real-time analytics with in-memory computing. Across these deployments some common architectural patterns have emerged. This whitepaper explains some of the most common use cases and challenges; the common technology components, including in-memory computing technologies; and how they fit into an IoT architecture. It also explains how Apache® Ignite™ (Ignite) and GridGain® are used for IoT.
Use Cases
This white paper will take a detailed look at the challenges faced by companies that have either used Redis and run into its limitations, or are considering Redis and find it is insufficient for their needs. This paper will also discuss how the GridGain in-memory computing platform has helped companies overcome the limitations of Redis for existing and new applications, and how GridGain has helped improve the customer experience.
Use Cases
This white paper will discuss the lack of in-memory capabilities in Apache® Cassandra™, why in-memory solutions make sense for today’s web and cloud applications, and how combining Cassandra with Apache® Ignite™ or GridGain can create an architecture that provides a substantial speed boost and a host of other benefits.
Use Cases
This white paper will help you understand how incorporating Apache Ignite into your architecture can empower dramatically faster analytics and transactions when augmenting your current MySQL® infrastructure.
Use Cases
Read this white paper and learn how financial services companies are using in-memory computing to address the technical challenges caused by new and recent financial regulatory initiatives
Use Cases
Fraud prevention is no simple task, and firms must tackle it simultaneously with other crucial tasks such as ensuring regulatory compliance. Fortunately, today’s in-memory technologies provide power tools for combatting fraud – tools that perform complex processing, modeling, and analysis of big data in real-time. This white paper discusses how firms are addressing fraud, and why in-memory computing technologies such as GridGain are perfectly suited to the task of detecting and stopping fraud.
Use Cases
This paper looks at the current state of high-frequency trading – why it’s popular and what types of strategies and technologies are being used – and then explores how in-memory computing can meet the technological challenges and increase profits within this market segment.
Use Cases
This white paper will discuss bitcoin and blockchain technology, describe the innovative opportunities this technology offers for financial services firms, and examine how in-memory options such as the GridGain in-memory computing platform can address the challenges and boost the effectiveness of tomorrow’s blockchain applications.
Use Cases
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.
Use Cases
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.

Application Notes
Learn how GridGain and Apache Ignite can 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.” It makes many Spark tasks simple, including stream ingestion, data preparation and storage, stream processing, state management, streaming analytics, and machine and deep learning.
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Learn how companies such as Expedia, HomeAway, JacTravel and TUI Group rely on GridGain and Apache Ignite In-Memory Computing Platforms to deliver a real-time, personalized, seamless end-to-end experience to their customers.
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Apache® Ignite™ includes full support for ANSI SQL-99. This overcomes a major weakness of other in-memory data grids that require developers to completely rewrite their SQL-based code. This application note explains Apache Ignite’s SQL Grid functionality and how to use it to combine the speed and scalability of in-memory computing with the power and flexibility of SQL.
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Reports and Guides

Access this third-party report by respected analyst firm The Taneja Group on the importance of GridGain’s approach to Big Data and Hadoop acceleration in particular.
Read EMA’s thorough coverage of how In-Memory Computing and Data Fabric technology are driving the growth of industries like finance, utilities and consumer retailing.
Download this informative Guide to In-Memory Computing and Data Fabric technology by Inside BIGDATA, one of the most authoritative publishers in the field of Big Data Analytics.
Download this insightful infographic showing the results of a survey of about 200 IT decision-makers — including project managers, network managers, software and business analysts, and other technology professionals working in the financial services industry.
Download this in-depth technical insight paper by respected IT analyst firm the Evaluator Group which covers how fast data technologies such as the In-Memory Data Fabric enable faster decision making and new business opportunities.
Access this essential guide to Hyperscaling your SaaS (or PaaS or IaaS) infrastructure through In-memory technology written by the leading Big Data publishing firm, Inside BIGDATA.