Graph-based solutions have been in the market for over a decade with deployments in financial services, healthcare, retail, and manufacturing. The graph technology of the past limited them to simple queries (1 or 2 hops), modest data sizes, or slow response times, which limited their value. A new generation of fast, scalable graph databases, led by TigerGraph, is opening up a new world of business insight and performance.
Join us, as we explore some new exciting use cases powered by native parallel graph database with storage and computation capability for each node:
• A large financial services payment provider is using graph-based pattern detection (7 to 11 hop queries) to detect more fraud and money laundering in real time, handling peak volume of 256,000 transactions per second.
• IceKredit, an innovative FinTech is transforming the near-prime and sub-prime credit market in United States, China and South Asian countries with customer 360 analytics for credit approval and ongoing monitoring.
• A biotech and pharmaceutical giant is building a prescriber and patient 360 graph and using multi-hop exploratory and analytic queries to understand the most efficient ways of launching a new drug for maximum return.
• Wish.com is delivering real-time personalized recommendations to increase eCommerce revenue.
Dr. Victor Lee is Senior Product Manager at TigerGraph, bringing together a strong academic background, decades of experience in the technology sector, and a strong commitment to quality and serving customer needs. His first stint in Silicon Valley was as an IC circuit designer and technology transfer manager, before returning to school for his computer science PhD, focusing on graph data mining. He received his BS in Electrical Engineering and Computer Science from UC Berkeley, MS in Electrical Engineering from Stanford University, and PhD in Computer Science from Kent State University. Before joining TigerGraph, Victor was a visiting professor at John Carroll University.
Graph databases have demonstrated the ability for organizations, from cutting-edge startups to global enterprises, to extract data intelligence that was next to impossible with traditional DBMS.
However, first-generation graph databases fall short when it comes to delivering the real-time performance and scalability required to build modern applications.
Memgraph is on a mission to fulfil the true potential of graph databases and open the doors to a whole new era of applications, by bringing to life a high-performance, horizontally scalable graph platform.
On this evening, we will take you through our journey building the world’s fastest and most scalable graph platform, describe new and exciting use-cases we’re working on, and conclude by giving you an insight into the future of real-time graph databases and the role they will play in powering the next generation of business applications.
Passionate software engineer. Founder and CEO of Memgraph, a high-performance graph database company based in London, UK. Passionate about building distributed systems, highly concurrent and lock-free algorithms and data structures. P.S. I love graphs!
- What are Graph Databases & what are typical use cases for this technology?
- How are Graph Database architectures changing as the space matures?
- What is coming next in the Graph Database market?
- How do Property Graphs differ from other graph technologies?
6:30pm - Arrival
7:00pm - Talks from Tigergraph and Memgraph
8:00pm - Pizza and Refreshments