Technical Presentations About GridGain and Apache Ignite

These technical presentations, developed and presented by GridGain in-memory computing experts, will help you understand, configure, and deploy the GridGain® and Apache Ignite® in-memory computing solutions. The presentations cover topics including in-memory computing, in-memory databases, stream processing, digital integration hubs, data lake acceleration, machine learning, deep learning, and how to apply these technologies and others to power digital transformation.

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. This webinar will explain with examples:
Learn more about the role of In-Memory Computing in supporting the real-time transactional, analytical and engagement needs for digital business and improving the customer experience.
Learn some of the current best practices in HTAP, and the differences between two of the more common technologies companies use: Apache® Cassandra™ and Apache® Ignite™.
By the end of the webinar, you will understand the most common in-memory computing options and how to choose the right in-memory technology based on your project needs.
How we accelerated the Machine Learning in Apache Ignite.
Learn why companies are choosing Apache Ignite and the enterprise-ready version of Apache Ignite from GridGain® to handle their in-memory computing needs, and moving away from traditional caches like Redis.
Learn how to get Apache Ignite native persistence up and running, and tips and tricks to get the best performance.
Apache Ignite is (an in-memory computing platform OR an in-memory distributed data store and compute grid) with full-fledged SQL, key-value and processing APIs. Many companies have added it as a cache in-between existing SQL databases and their applications to speed up response times and scale. In other projects they've used it as its own SQL database. 
Join Fotios Filacouris, GridGain Solution Architect, as he discusses how you can supplement PostgreSQL with Apache Ignite. You'll learn:
Machine learning is a method of data analysis that automates the building of analytical models. By using algorithms that iteratively learn from data, computers can find hidden insights without the help of explicit programming. These insights bring tremendous benefits to many different domains.
If you are trusting a single datacenter to support your newest mission critical or cutting edge in-memory computing application, you may want to reconsider your strategy. No datacenter is 100% secure against natural disasters, hackers or just plain old human error.  In order to maintain all the 9s of availability that you have promised, you need to hedge your bets on…