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.
GridGain offers highly responsive, reliable managed services – known as GridGain Nebula – for the Apache Ignite or GridGain in-memory computing platforms at a fraction of the cost of staffing an internal team. We can manage your environment 24x7, whether on-premises, on a private or public cloud, or on a hybrid environment. Download the datasheet to learn more.
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....
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.
This white paper provides insight on improving the scale, speed, and agility of MySQL so that it can support the digital transformation initiatives of today's enterprises. New business needs and performance demands have pushed many applications beyond MySQL's (and other RDBMSs) architectural limits. In many cases, the issues cannot be remedied by just fixing MySQL.
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 the best practices for delivering new applications and APIs with in-memory computing, and how it helps open up existing systems, become more agile, and deliver unlimited speed and scale. This eBook is Part 3 of the best practices for digital transformation series.
Digital Integration Hubs (DIH) solve a key challenge enterprises face when driving toward real-time business processes in an environment where data is spread across disparate databases. The GridGain in-memory computing platform has proven to be a key component of DIH architectures. Download the application note to learn more about the Digital Integration Hub…
The high performance GridGain platform is ideal for
digital transformation use cases. However, some low
latency/high transaction volume scenarios, such as in
the financial services and telecommunications industries,
strain the capabilities of standard Java Virtual
Reports and Guides
Digital transformation is requiring organizations of all types to explore opportunities to leverage data in the next normal and compete in the digital economy.
The 451 Take is that GridGain continues to increase in size and expand its platform with new, differentiating features.
Last year in particular was strong for the company, especially in terms of recurring revenue growth
and the number of new features released.