How IMC Powers next Generation Trading
IMC Summit North America 2018 – Kevin Goldstein
Wall Street’s Big Banks Are Waging an All-Out Technological Arms Race. They are battling to control the $58 billion-a-year equities industry.
Kevin Goldstein, Principal Architect at Neeve Research will discuss the in-memory architectures that enabled him to build very fast, reliable, and scalable enterprise applications, but more importantly, enables him to build and maintain them easily and in an agile manner. The move towards in-memory computing was to meet ever-increasing demands on performance. Kevin has been instrumental in seeing this shift unfold mostly through the adoption of in-memory architectures that tackle not just the data side of the equation, but also the messaging and processing side of applications. Breakthrough performance and reliability have been achieved with an in-memory equities platform delivering one million ‘Client to Market’ transactions per second (TPS) at < 10 microseconds ‘Client to Market’ latency, with no performance change, going from zero to peak traffic, and with zero data loss guaranteed. In-memory solutions, with its minimal hardware footprint, goes even further to reduce massive investments in capital equipment resulting in significant saving.
Powering Digital Transformation with IMC
IMC Summit North America 2018 – Becky Wanta
Join Becky Wanta, COO/CIO of One Degree World (ODW) and former CIO/CTO/Chief Innovation Officer of MGM; Global CTO of Pepsico, BestBuy, Southwest Airlines, Wells Fargo, and Wellpoint Health to see what she has to say about enabling business agility.
Becky will discuss how the impact of in-memory computing was immediate, and the cornerstone to delivering a vision that disrupted her industry and remains unmatched with the competition today. Imagine the disruption of staid industries like Travel, Entertainment, Financial Services and Healthcare where new markets made achievable via an in-memory core infrastructure with high performance and high availability. Performance intensive applications/new capabilities (IoT, Omnichannel, Artificial Intelligence, Machine Learning, Blockchain, Augmented and Virtual Reality) are delivered ahead of the competition in days versus years while abstracting the complexity of the back-end legacy environments to support this speed-to-market.
Real Time with AI – The Convergence of Big Data and AI
IMC Summit North America 2018 – Colin MacNaughton
Big data is moving to a new stage of maturity — one that promises even greater business impact and industry disruption over the course of the next few years. As big data initiatives mature, organizations are now combining the agility of big data processes with the scale of artificial intelligence (AI) capabilities to accelerate the delivery of business value.
The convergence of big data with AI has emerged as the single most important development that is shaping the future of how firms drive business value from their data and analytics capabilities.
Making AI real-time to meet mission-critical system demands put a new spin on your architecture. We all know that the deeper the data the better the results and the lower the risk. However, doing thousands of computations on big data requires new data structures and messaging to be used together to deliver real-time AI. During this session will look at real reference architectures and review the new techniques that were needed to make AI Real-Time.
Real-Time with AI – The Convergence of Big Data & AI - Synerzip Webinar
The Convergence of Big Data and AI Big data is moving to a new stage of maturity — one that promises even greater business impact and industry disruption over the course of the next few years. As big data initiatives mature, organizations are now combining the agility of big data processes with the scale of artificial intelligence (AI) capabilities to accelerate the delivery of business value.
“Hybrid Transactional Analytical Processing (HTAP)” The Key to Intelligent Systems
Machines are getting stronger, software is getting faster, and data is getting bigger.
The X-Platforms’ novel approach to stream processing and state management makes it unique in this problem space. HTAP requires massive amounts of data, and it needs to process it with sub-millisecond latencies, which is what our platform was built for. Coupled with our high-availability model, we let you perform this analysis with the confidence that your systems will have full redundancy and five-nine’s availability.
Join us to discuss HTAP/Translitical processing, how to leverage memory and state, and see how the X-Platform fits into this landscape allowing you to write highly available systems that serve out millions of transactions where latencies are measured in microseconds.
Real-Time with AI - The Convergence of Big Data and AI
Big data is moving to a new stage of maturity — one that promises even greater business impact and industry disruption over the course of the next few years.
The convergence of big data with AI has emerged as the single most important development that is shaping the future of how firms drive business value from their data and analytics capabilities. Digital capabilities have moved data from batch to real-time, on-line, always-available access.
Making AI real-time to meet mission-critical system demands put a new spin on your architecture. During this session we will look at real reference architectures and review the new techniques that were needed to make AI Real-Time.
Easy Exactly Once Guaranteed Processing For You Stream
Today’s Processing must be fault tolerant and continuously adapt to changing data flows.
Distributed systems typically offer several levels of guaranteed message delivery. Most streaming architects often deploy a distributed message platform with an at least-once guarantee, which guarantees that the message will be sent, but with the caveat that it’s possible some messages may be duplicated. These cases where you can get the same message twice is a very typical distributed system problem when networks are unreliable.
In today's mission critical streaming applications performance matters when dealing with streaming data, in-memory processing, and in-memory data is key. Keeping data in motion is important for the application performance. Organizations building real-time stream processing systems need to use an in-memory paradigm and be able to use any message broker and trust the platform to deliver each message exactly once.
Learn how to build in-memory applications on streaming data that do exactly one guaranteed processing without you having to code the needed guarantees into the applications. We will discuss how to build, monitor, and manage ultra-high performance, fault tolerant stream-based systems with extreme ease.
Using In-Memory Computing to Convert Big Data Into Fast Data
Deploying Big Compute applications can lead to a wide range of tools and approaches needed to run large-scale applications for business, science, and engineering using a large amount of CPU and memory resources in a coordinated way. To really succeed, the data itself must be scaled just as wide. The immediate problem is that in many cases, the speed at which you get results matters just as much as the results themselves.
For a business to really get the value they need from Big Compute, you need to shift the paradigm and toolset to a message based, stateful data architecture with distributed computations.
We will walk through how the paradigm shift happened and where IMDG’s, NoSQL and In-Memory databases stopped working and what else was needed.
Getting Started with X Platform Tutorials
X-Platform micro-tutorials are very small tutorials designed to get developers up and running using the X-Platform as quickly as possible. This tutorial should be used in conjunction with the Talon Getting Started Guide.
Lesson #1: Setting Up Your Development Environment
This brief tutorial will walk you through the ease of setting up an environment for your first X Platform application. We will get your Eclipse setup in preparation for our first project
Lesson #2: First State Replication Project
Use maven to generate your first state replication project, modify the messages being sent, add some additional functionality and run it from eclipse.
05/22 Microservices: What are they and why are they so hard to write?
The webinar discusses the following
How to wire multiple services together
How to handle failures
How to build event driven architectures easily
How to do transaction processing in a multi-agent world
05/08 Fire & Forget: How to Build IoT Message-based Microservices Apps
Some topics discussed
How to leverage memory and state
Building HA systems
12/14 Webinar - Build real-time dynamic pricing apps without compromise
This webinar demonstrates
How to easily build dynamic/competitive pricing capabilities that scale to meet business growth
More about key dynamic pricing elements in analytical/intelligent transactional applications
01/18 Webinar - Build and leverage value based pricing to drive revenue
The speed of delivery and latency are key to competitive eCommerce and mission-critical capabilities.
Leverage Competitive Personalized Pricing and Offer Management
Build and Deploy Real-time Value-Based Pricing
How to build customer value-driven pricing capabilities and leverage data integration to provide optimal real-time offers
In-Memory Computing Summit 2017 - In Memory and Microservices - The Challenges and Advantages
In this video, Niranjan Dhomse, Principal Architect at Neeve Research begins with a quick review of the essence of microservices and then looks at the most common challenges with microservice architectures and how using an in-memory paradigm will help. Using recent use cases, he explores how in-memory microservices have solved many of the most common issues and what developers and architects can expect from the microservices framework. The session concludes with a live coding session focused on the steps you will want to follow when building, deploying and managing in-memory microservices to make sure they are performant, scalable and developed quickly.
In-Memory Computing Summit 2017 - Hybrid Transaction: Analytical Processing "HTAP" What is it and Why It Matters
In this video, Colin MacNaughton, Head of Engineering at Neeve Research discusses how this convergence and intersection of artificial intelligence, big data, and transactional processing has delivered significant digital transformation in advertising, e-commerce, fraud detection and logistics.
Colin presents the ideal HTAP scenario, why traditional DBMS fail to deliver HTAP, and how to successfully architect in-memory HTAP solutions. The emergence of HTAP means as an IT leader you must identify the value of advanced real-time analytics, and where and how these can enable process innovation in your organization. By eliminating analytic latency and data synchronization issues, HTAP will enable you to simplify your information management infrastructure and overcome the challenges of adopting this new approach.
9/26 Webinar - Extreme Transaction Processing In a Memory Oriented World
Transactional systems must be fast, always available and scale to meet the ever-changing needs of the business. It's now commonplace for:
E-commerce systems to demand single digit millisecond response times,
Trading systems to require latencies in the order of microseconds, and
Gaming or analytic engines to consume hundreds of thousands of transactions a second.
A common mistake is to try to meet these extreme needs by just replacing traditional disk based storage systems with in-memory data grids and traditional application architectures. Instead, we need to think differently about how such systems are architected and employ techniques to unlock the full potential of memory oriented computing.
8/29 Webinar - Building Fraud Detection using HTAP
Fraud detection and other streaming/transactional systems that leverage AI and rules based big data fit into the area Gartner calls HTAP (Hybrid Transactional Analytical Processing). “When business moments are transient opportunities that must be exploited in real time, HTAP allows advanced analytics to be run in real time on "in flight" transaction data, providing an architecture that empowers effective response to business moments.” Business leaders can be informed of real-time issues, outcomes, and trends that necessitate action, such as in the areas of public safety, risk management, and fraud detection.
8/3 Webinar - 8 Steps to Building and Deploying Microservices Architectures
As organizations embark on their digital transformation, moving to a microservices architecture is key in meeting business challenges and staying ahead of the game. Problems arise and quick solutions are needed to ensure architectures deliver results without sacrificing performance and speed.
During this webinar Girish Mutreja, CEO and Author of the X Platform™, discusses why industries are shifting to microservices based architectures and the potential limitations that can occur during building and deployment. The webinar also features 8 steps for easy development using the revolutionary X Platform™.
6/27 Webinar - IoT Application Challenge
Tom Lee, Principal Architect at Neeve Research, demonstrates how to build fire-and-forget message based microservices applications for IoT. This webinar shows
How to easily write IoT applications that are more dynamic and faster
Direction for building scalable stream processing applications with extreme performance and without non-functional compromise
Simple deployment and monitoring best practices
Tom also presents a live demo showing how to reduce development time, improve performance, and deploy applications faster!
5/9 Webinar - Exactly Once Streaming
Even the most advanced software engineers and streaming products struggle to ensure every event in a stream (or transaction) is processed with 100% accuracy in sub-millisecond speed. This interactive webinar features Colin MacNaughton, Head of Engineering at Neeve Research, and Igor Mihaljevic from Kode 41, as they share new techniques for accomplishing this in the context of an Ad Exchange application. The presenters are two of the best low latency and distributed system engineers in the industry and have solved various challenges for mission critical systems at Fortune 300 organizations.
3/28 Webinar - Microservices in Microseconds
The Microservices application architecture pattern is rapidly being adopted across enterprises. This webinar features Girish Mutreja, CEO at Neeve Research, as he walks through microservices, the benefits of implementing a microservices architecture, and how the X Platform™ allows one to reap the full benefits of a microservices based architecture.
In-Memory Computing Summit 2016 - Best Innovation Presentation
Neeve Research was proud to receive the award for, "Best Innovation Presentation at IMC 2016". This presentation provides an overview of the Neeve Research - X Platform™ and how the platform has harnessed the speed of in-memory computing.
In-Memory Computing Summit 2016 - Extreme Transaction Processing in a Memory Oriented World
Modern transactional systems need to be fast, always available and constantly scale to meet the ever changing needs of the business. It is becoming increasingly commonplace for next generation e-commerce systems to demand double or single digit millisecond response times, for financial trading systems to incur maximum latencies in the order of microseconds and gaming and analytic engines to consumes hundreds of thousands of transactions a second. It is a common and tempting mistake to believe that we can meet the extreme needs of such systems by just replacing traditional disk based storage systems with in-memory data grids using traditional application architectures. Such an approach will take us only so far after which the system’s demands will once again overtake its capabilities. To truly meet the extreme needs of these systems and continue to scale as the demand scales, we need to think differently about how such systems are architected and employ modern techniques to unlock the full potential of memory oriented computing. This talk, by Girish Mutreja, explains why and how.