Learn About In-Memory Computing
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 an active - active or active - passive set up. The GridGain Multi-Datacenter Replication feature makes doing this a snap.
Machine learning is a method of data analysis that automates the building of analytical models. By using algorithms that iteratively learn from data, computers are able to find hidden insights without the help of explicit programming. These insights bring tremendous benefits into many different domains. For business users, in particular, these insights help organizations improve customer experience, become more competitive, and respond much faster to opportunities or threats.
PostgreSQL is one of the most popular open source RDBMSs. Apache® Ignite™ is the leading open source in-memory computing platform. The Apache Ignite distributed computing platform is inserted between the application and data layers and works with all common RDBMS, NoSQL and Hadoop® databases to provide speed, scale and high availability. When Postgres comes up short, Ignite may be able to help you bridge the gap. Join Fotios Filacouris, GridGain Solution Architect, as he discusses how you can supplement PostgreSQL with Apache Ignite. You'll learn:
During this 1-hour webinar, GridGain Product Manager and Apache® Ignite™ PMC Chair Denis Magda will discuss a Fast Data solution that can receive endless streams from the Interne
Apache® Ignite™ is the leading open source in-memory computing platform. Apache Ignite is deployed between the application and data layers and works with all common RDBMS, NoSQL and Hadoop® database to provide speed, scalability and high availability. In this presentation, GridGain Product Manager and Apache Ignite PMC Chair Denis Magda will explain featured of the Apache Ignite distributed computing platform which are important for financial use cases, including:
If downtime is not an option for you, and your application needs to be extremely low-latency, Kubernetes® and Apache® Ignite™ are open source frameworks that work exceedingly well together to achieve these goals.
It’s well known that there is a tradeoff between data consistency and high availability. But at the same time, there are lots of applications that still require very strong consistency guarantees, and making such applications highly available can be quite a challenge.
Telecommunications is no longer as simple as connecting a bunch of wires and physically maintaining them in order to deliver a dial tone. Today’s telecommunications providers face myriad challenges around big data and analytics. Data, and unlimited data plans, is stretched telco networks to provide capacity and services that no one had dreamed of even 15 years ago. Telcos are constantly monitoring and upgrading networks to support the insatiable hunger for data. The network is only part of the answer though.
Akmal B. Chaudhri
There is a myth that online financial operations need to be delegated to relational databases due to their ACID transaction support. But today, most of these disk-based relational databases cannot keep pace with the rapidly growing volumes of data that are becoming a bottleneck in the overall transactional system. There are two solutions to deal with this issue: upgrade to more expensive hardware or migrate to a distributed platform.
Ever-changing financial regulatory compliance policy is causing unprecedented and growing technical challenges. Banks and other financial institutions must continuously monitor, collect, and analyze vast amounts of data from multiple, disparate sources in real-time. Coping with these challenges in an efficient way requires not only an extremely fast, scalable, and cost-effective data technology, but also one that can incorporate and handle new requirements as they arise.
GridGain 8.1 is a turnkey release which makes GridGain and Apache® Ignite™ the only platforms on the market that combine a distributed SQL database with an in-memory key-value data grid.
Eric Karpman, Matt Sarrel
Data is critical to the success of financial services companies. Market data, customer data, trade data, and compliance data are retained, processed and analyzed to help firms not only stay afloat but also ahead of the competition. During this webinar, we will discuss the different types of financial data, ways financial and fintech companies process it, and show how in-memory computing is used to instantaneously analyze and make decisions based on internally and externally available data. We will discuss:
Join GridGain Systems Product Manager Denis Magda as he introduces the newest features in Apache Ignite 2.0 including the dramatically improved memory architecture and enhanced SQL DDL support. Apache Ignite 2.0 is a turnkey release which blends a distributed in-memory SQL database (IMDB) and an in-memory key-value data grid (IMDG) under one data management platform. It is also a necessary stepping stone ahead of the Apache Ignite 2.1 release which will be focused around native disk persistence, allowing Ignite operate equally well in-memory and on-disk.
Rachel Pedreschi, Matt Sarrel
In-memory computing brings unlimited performance and scalability to even the most demanding business applications and their accompanying data sets. Moving data from disk to memory brings enormous performance gains. Boosting performance and scalability is of great value as it makes existing applications better and paves the way towards a memory first architecture that opens new horizons in computing.
Nikita Ivanov, Jason Stamper
In this webinar hosted by GridGain Systems and 451 Research, you’ll hear about the compelling drivers for in-memory computing technologies: especially in-memory databases, data grids, and platforms. 451 Research’s data platforms analyst Jason Stamper will explain how in-memory computing helps to overcome many of the challenges faced by the modern enterprise when it comes to data processing and analytics. He will also gaze into his crystal ball to predict how in-memory computing technologies will evolve in coming years.
The Internet of Things (IoT) is more than a bunch of sensors. Sensors and embedded devices gather data about the surrounding environment, but what you do with this data is what truly matters. A bunch of sensors won’t optimize your business. Collecting and analyzing the data that those sensors produce will.
Eric Karpman, Matt Sarrel
The Insurance industry is undergoing significant changes. In addition to economic and political uncertainty, insurers face investment income pressure from low interest rates. Coupled with this are the challenges of social and regulatory changes based on new customer expectations and government and employer policies.
Learn how to use an in-memory computing platform like Apache® Ignite™ and GridGain to develop high performance and highly scalable mobile apps in this webinar.
Service-oriented architectures (SOAs) are used to build flexible, independently deployable software systems. Microservices decompose services down to small pieces and use lightweight protocols to allow processes to communicate with each other over a network. This architectural approach is becoming increasingly popular, especially in high-availability systems. However, microservices-based solutions can become victims of their own success as greater and greater demands are placed on the systems that use them.