Technical Papers for Developers
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.
Omnichannel banking needs a single, real-time view of the customer that is shared across channels. Companies use the GridGain in-memory computing platform to create infrastructure for 10x or greater digital channel loads, proactively personalize and improve the customer’s experience, and allow real-time analytics and automation. This Industry Brief tells you how.
This in-depth feature comparison shows how the most current versions of GridGain Professional Edition, Enterprise Edition, Ultimate Edition and Oracle Coherence (and their respective open source projects where relevant) compare in 25 different categories.
This white paper discusses how in-memory computing is helping companies address increasing mobile application usage, real-time data needs, improving the customer experience, fraud prevention, compliance, and other requirements to modernize and accelerate payment solutions.
International Bank Counts on HPC and Fast Data with GridGain® A leading international bank offering investment advisory and wealth management services to private and institutional clients around the world was looking to upgrade its custom-built software system to a High Performance Computing (HPC) solution.
Reports or 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.
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:
Bitcoin and blockchain, the digital-ledger technology behind this electronic currency, are generating enormous amounts of interest in the financial services industry. Most of the larger banks are investigating this area, and many technology companies are building platforms to enable blockchain technology for financial services firms.
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 architecture with…
Reports or Guides
This is a comprehensive 12-page guide written by respected analyst Daniel Gutierrez from InsideBIGDATA, which reveals the key knowledge you’ll need to begin implementing the in-memory computing technology necessary to hyperscale your SaaS infrastructure.
Learn how high-performance in-memory computing architecture is rapidly becoming the method of choice for today’s real-time applications that are focused on big data, fast data, streaming analytics or machine and deep learning.
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....
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.
Leading banks, asset management firms, and fintech companies rely on the GridGain in-memory computing platform as a foundation for real-time risk analytics, portfolio management, and regulatory compliance. These companies use Gridgain to achieve a common, real-time view of risk by bringing together many types of information. Download this Industry Brief to learn how.
Compares GridGain and Terracotta features in 22 key areas: in-memory data grid functionality, caching, data querying, transactions, security and more.
This white paper discusses how an in-memory computing platform solution like GridGain gives financial services companies the speed, scalability, and flexibility they need to build successful IoT-based applications and services.
The GridGain In-Memory Computing Platform powers e-Therapeutics’ Network Pharmacology platform so that they can identify and analyze specific networks of proteins associated with a particular disease based on computational analysis of disease cells. While performing a single analysis is relatively straightforward and does not take a lot of time, the e-Therapeutics approach…
Reports or Guides
The continued emergence of data ecosystems built on active metadata and data fabrics will enable efficiency, automation, augmentation, financial governance and sustainability. Data and analytics leaders should use these predictions to plan for and invest in an ecosystem-driven future.