Webinars for Developers
GridGain® webinars present information on a variety of in-memory computing topics, and are often co-hosted with other in-memory computing customers or thought leaders. Topics include in-depth analyses and recommendations for common issues faced by in-memory computing developers, enterprise architects, CIO/CTOs, and other enterprise decision-makers. Different approaches for implementing solutions are reviewed, including solutions using the GridGain in-memory computing platform and Apache® Ignite™. The webinars cover enterprise use cases such as high-frequency trading, omnichannel customer engagement, the Internet of Things (IoT), financial services, application performance and scaling, fast data, and more.
All GridGain webinars are archived and available for free online.
Attendees will be introduced to the fundamental capabilities of in-memory computing platforms (IMCPs). IMCPs boost application performance and solve scalability problems by storing and processing unlimited data sets distributed across a cluster of interconnected machines.
With most machine learning (ML) and deep learning (DL) frameworks, it can take hours to move data and to train models. It can also be hard to scale with data sets that are increasingly frequently larger than the capacity of any single server. The size of the data can also make it hard to incrementally test and retrain models in near real-time to improve business results.
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:
Deployment models for Apache Ignite® and applications connected to it vary depending on the target production environment. A bare metal environment provides the most flexibility and fewer restrictions on configuration options.
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.
To take full advantage of an in-memory platform, it’s often not enough to upload your data into a cluster and start querying it with key-value or SQL APIs. You need to distribute the data efficiently and tap into distributed computations that minimize data movement over the network.
Apache Ignite is a powerful in-memory computing platform. The Apache IgniteSink streaming connector enables users to inject Flink data into the Ignite cache. Join Saikat Maitra to learn how to build a simple data streaming application using Apache Flink and Apache Ignite.
If you experience limitations with the size, scale or performance of your relational database, it may be time to migrate to a distributed system. Apache Ignite is a distributed platform that can function as a database, providing both SQL and JCache APIs to work with your data.
In this webinar you will learn how to use the service grid capabilities of the Apache Ignite distributed in-memory computing platform. Simple code examples will help us review possible architectural solutions and demonstrate how to build fault-tolerant, scalable and flexible systems.
Most enterprises have PostgreSQL deployments that they will be using for years to come for transactional, big data, mobile, and IoT use cases. How can Postgres continue to support the current and emerging use cases which demand ever higher performance and more scalability into the future?
Learn some of the best practices and the different options for maximizing availability and preventing data loss. This session explains in detail the various challenges including cluster and data center failures, and the best practices for implementing disaster recovery (DR) for distributed in-memory computing based on real-world deployments. Topics include:
This webinar discusses deploying Apache Ignite into production in public and private clouds. Companies have faced many challenges when deploying in-memory computing platforms such as Apache Ignite in the cloud, but they have also discovered many best practices that have made success possible.
Learn how to monitor various components of a distributed cluster for network, memory, or node-specific issues, and troubleshoot to resolve issues. By the end of this session you'll have a handy checklist and set of tools to consider using for your own deployments.
Learn how combining Apache Ignite with a Relational DBMS can offer enterprises the best of both open-source worlds. This webinar will discuss how this combination produces a highly-scalable high-velocity grid-based in-memory SQL database, with a robust fully-featured SQL persistent datastore for advanced analytics and data-warehouse capabilities.
In this webinar Alexey Zinoviev, Apache Ignite ML contributor for GridGain will talk about new 2.7 release of Apache Ignite and present the new features that are added to Ignite ML modules.
In the second phase of his presentation he will introduce what a Java programmer needs to do and understand in a typical Big Data and ML projects.
Learn how companies have been using GridGain and Apache Ignite to add in-memory speed and unlimited horizontal scale to SQL with no rip-and-replace of the underlying database.
Regardless of how mature a data storage technology is, backing up data is a laborious and difficult task that can cost us time, increase our stress levels and jeopardize our jobs. During this webinar, you will learn how to perform data snapshot without impacting ongoing user activities, how to perform a snapshot whilst keeping data consistent and transactionally complete…