GridGain Resources for Architects

Access Our Library of In-Memory Computing Resources

GridGain produces a wide selection of resources that can help you understand how our in-memory computing platform can fit within your existing or new architectures. Whether your organization needs to speed up and scale out an existing application or you are focused on the development of a new, modern application architecture, our resources can help you understand how GridGain can help. Select from our extensive library of white papers, webinars, case studies, application notes, ebook and more.

Resources

Accelerate Apache Cassandra for Extreme OLTP Workloads with GridGain

This white paper discusses how to accelerate Apache® Cassandra™ and improve Cassandra performance. Apache Cassandra is a popular NoSQL database that does certain things incredibly well. It can be always available, with multi-datacenter replication. It is also scalable and lets users keep their data anywhere. However, Cassandra is lacking in a few key areas – particularly speed. Because it stores data on disk, Cassandra is not fast enough for some of today’s extreme OLTP workloads.

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High Performance, Real-time Data Architecture for the Internet of Things
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.
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Driving High-Frequency Trading with In-Memory Computing
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.
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Improving Speed and Scalability with In-Memory Data Grids
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.
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Achieving Real-Time Financial Regulatory Compliance with In-Memory Computing
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
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Introduction to Apache Ignite
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.
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In-Memory Computing: Leading the Fast Data Revolution

In-memory computing is driving a revolution that will change human society. With solutions that allow Big Data to reside in RAM across a cluster of nodes for massive parallel processing, data insights are becoming possible at unprecedented speed and scale with costs well within reach. These new capabilities allow real-time insights from transactional data, turning Big Data into Fast Data.

Today’s in-memory computing features include:

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Designing Multi-Cluster In-Memory Computing Applications
This 1-hour webinar presented by GridGain System’s Sr. Technical Consultant Lucas Beeler will discuss architectural best practices many companies have used in their journey to multi-cluster computing applications.
GridGain® Cloud: In-Memory Computing Deployed In Minutes

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:

Apache® Ignite™ Best Practices: Cluster Topology Management and Data Replication
When deployed properly, it's hard to beat a horizontal distributed architecture's scalability, availability and reliability. The trick is deploying it properly to compensate for individual node, data or network failures. Learn some of the best practices for setting up your clusters properly to maximize availability, reliability and flexibility for future needs.
Les essentiels d’In-Memory Computing pour les architectes et les développeurs, Partie 2
Lors de ce Webinar en Anglais, Akmal Chaudhri, Promoteur des Produits GridGain System et Apache® Ignite™, présentera les capacités et les composantes fondamentales de la plateforme d’In-Memory Computing avec Apache Ignite et vous expliquera comment passer de la théorie à la pratique. Grâce à des exemples de plus en plus codés, les architectes et développeurs apprendront :Le traitement colocalisé, Le traitement colocalisé pour l’informatique distribuée,Le traitement colocalisé pour les SQL (raccords distribués et autres), L’usage distribué permanent.  
Les essentiels de l’In-Memory Computing pour les architectes et les développeurs – Partie 1
Lors de ce webinar, Akmal Chaudhri, Promoteur de Produit pour GridGain Systems, présentera les capacités et les composantes fondamentales de la plateforme d’In-Memory Computing avec Apache Ignite et vous expliquera comment passer de la théorie à la pratique.
Best Practices for Deploying Distributed Databases and In-Memory Computing Platforms with Kubernetes
Learn how Kubernetes can orchestrate a distributed database or in-memory computing solutions using Apache Ignite as an example.
In-Memory Computing Essentials for Architects and Developers: Part 2

In this webinar, Akmal Chaudhri, Technology Product Evangelist for GridGain and Apache Ignite, will introduce the fundamental capabilities and components of a distributed, in-memory computing platform. With increasingly advanced coding examples, architects and developers will learn about:

In-Memory Computing Essentials for Architects and Developers: Part 1

In this webinar, Akmal Chaudhri, GridGainTechnical Evangelist, will introduce the fundamental capabilities and components of an in-memory computing platform with a focus on Apache Ignite, and demonstrate how to apply the theory in practice. With increasingly advanced coding examples, architects and developers will learn about:

  • Cluster configuration and deployment
  • Data processing with key-value APIs
  • Data processing with SQL

This is Part 1 of a 2-part webinar series designed for software developers and architects.

Building New Hybrid Transactional/Operational Processing (HTAP) Applications With Apache® Ignite™

Once you've put in-memory computing in place to add speed and scale to your existing applications, the next step is to innovate and improve the customer experience. Join us for part 2 of the in-memory computing best practices series. Learn how companies build new HTAP applications with in-memory computing that leverage analytics within transactions to improve business outcomes. This is how many retail innovators like Amazon, Expedia/HomeAway or SaaS innovators like Workday have succeeded. This webinar will explain with examples on how to:

Adding Speed and Scale to Existing Applications with No Rip and Replace Using Apache® Ignite™

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.