Learn About In-Memory Computing
In this 1-hour webinar, GridGain Systems Chief Product Officer Dmitriy Setrakyan will present how distributed memory-centric architectures can be applied to various financial systems.
In this webinar, Denis Magda, GridGain Director of Product Management and Apache Ignite PMC Chairman, will introduce the fundamental capabilities and components of a distributed, in-memory computing platform. With increasingly advanced coding examples, you’ll learn about: Collocated processing Collocated processing for distributed computations Collocated processing for SQL (distributed joins and more) Distributed persistence usage This is Part 2 of a 2-part webinar series designed for software developers and architects.
In this webinar, Denis Magda, GridGain Director of Product Management and Apache Ignite PMC Chairman, will introduce the fundamental capabilities and components of an in-memory computing platform, and demonstrate how to apply the theory in practice. With increasingly advanced coding examples, you’ll learn about:
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
Akmal B. Chaudhri
Learn how to boost performance 1,000x and scale to over 1 billion transactions per second with in-memory storage of hundreds of TBs of data for your SQL-based applications. Apache Ignite is a unique data management platform that is built on top of a distributed key-value storage and provides full-fledged SQL support. Attendees will learn how Apache Ignite handles auto-loading of an SQL schema and data from a Relational DBMS, supports SQL indexes, supports compound indexes, and various forms of SQL queries including distributed SQL joins. Examples will show:
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:
Akmal B. Chaudhri
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.
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.
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.