CTOs/CIOs Use GridGain to Accelerate and Massively Scale Applications
CTOs and CIOs are increasingly initiating digital transformations to drive better business decision making and performance. Meeting new customer experience requirements requires improving applications to deliver real-time performance and massive scalability. Getting access to data in real-time allows your business to make better decisions. In-memory computing is the answer for businesses pursuing digital transformation. Deploying effective in-memory computing solutions in time and within budget requires a trusted technology partner.
GridGain In-Memory Computing Solutions
GridGain offers the in-memory computing platform software, support, and professional services you need to better achieve your real-time digital transformation technical challenges. The GridGain in-memory computing platform easily integrates with your new or existing applications and provides real-time performance and massive scalability.
Built on the open source Apache Ignite project, GridGain is a cost-effective solution for accelerating and massively scaling out new or existing applications with users that span a wide variety of use cases and industries.
The GridGain in-memory computing platform easily integrates with your systems, deployed as an in-memory computing layer between the application and data layer of your new or existing applications. GridGain can be deployed on-premises, on a public or private cloud, or on a hybrid environment.
The GridGain In-Memory Platform Helps CTOs and CIOs Achieve Goals
For existing applications, GridGain is typically used as an in-memory data grid between the application and data layer, with no rip-and-replace of the underlying database. For new applications, GridGain is used as an in-memory data grid or an in-memory database. A Unified API provides easy integration with your existing code with support for SQL, Java, C++, .NET, Scala, Groovy, and Node.js, enabling you to create modern, flexible applications built on an in-memory computing platform which will grow with your business needs. GridGain includes ANSI-99 SQL and ACID transaction support.
Learn How GridGain Provides In-Memory Computing Solutions for CTOs and CIOs
The white papers, webinars, application notes, product comparisons, and videos below discuss the business benefits for CTOs and CIOs looking for in-memory computing solutions.
Managing distributed systems can be complex and time consuming because there are numerous moving parts. Having a consistent set of tools can give a clear picture of how clusters are performing, when to take action and avoid potential problems, and how to optimize configurations.
Mythili, IBM Distinguished Engineer, will discuss increasing market pressures in key industries such as banking which are leading Z platform users to leverage Digital Integration Hubs for flexible information flow between core transactional systems and hybrid cloud environments. Digital Integration Hubs efficiently integrated with systems of record can significantly accelerate digital transformation journeys and deliver reduced complexity, high throughput, and low latency.
If your company is in an industry such as ecommerce, logistics, online learning, food delivery, or online business collaboration, you may be seeing a huge spike in your business which is straining the limits of your customer-facing or internal applications. If you need to speed up and scale out your applications, one of the fastest approaches is to deploy an in-memory data grid.
When working with multiple data centers, it is important to ensure high availability of your GridGain cluster. The GridGain Enterprise and Ultimate Editions, built on Apache Ignite®, include a Data Center Replication feature that allows data transfer between caches in distinct topologies, even located in different geographic locations.
Using code examples, we will cover the following topics:
The Apache Ignite transactional engine can execute distributed ACID transactions which span multiple nodes, data partitions, and caches/tables. This key-value API differs slightly from traditional SQL-based transactions but its reliability and flexibility lets you achieve an optimal balance between consistency and performance at scale by following several guidelines.
Apache Ignite can function in a strong consistency mode which keeps application records in sync across all primary and backup replicas. It also supports distributed ACID transactions that allow you to update multiple entries stored on different cluster nodes and in various caches/tables. In addition, consistency and transactional guarantees are put in effect for memory and disk tiers on every cluster node.
Apache Ignite 2.8 includes over 1,900 upgrades and fixes that enhance almost all components of the platform. The release notes include hundreds of line items cataloging the improvements. In this webinar Ignite community members demonstrate and dissect new capabilities related to production maintenance, monitoring, and machine learning including:
Attendees will be introduced to the fundamental capabilities of in-memory computing platforms (IMCPs) in this Apache Ignite tutorial. IMCPs boost application performance and solve scalability problems by storing and processing unlimited data sets distributed across a cluster of interconnected machines.
Apache Ignite® and GridGain® allow you to perform fast calculations and run highly efficient queries over distributed data. Both Ignite and GridGain provide a flexible configuration that can help you make cluster operations more secure. In this webinar, we will cover the following security topics:
- The secure connection between nodes (SSL/TLS)
- User authentication
- User authorization
Using live examples, we will go through the configurations for:
Change Data Capture (CDC) has become a very efficient way to automate and simplify the ETL process for data synchronization between disjointed databases. It is also a useful tool for efficient replication schemas. We will cover the fundamental principles and restrictions of CDC and review examples of how change data capture is implemented in real life use cases. By the end of this session you will understand:
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This eBook explains the best practices for adding speed and scale to existing applications that offer the least disruption and help meet the long term goals of transforming the business. Performance and scalability challenges exist because of the adoption of new customer-facing Web and mobile channels, of new technologies such as the Internet of Things (IoT), and of new types of data including social and machine data. Their increased adoption has driven up transaction, query, and data volumes, as well as the new for real-time responsiveness.
This eBook explains how to:
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: