Among the early deployments of graph technology are cloud and fintech vendors specializing in real-time intelligence tools for trading and risk management. The shift to graph technologies is propelling new trading platforms based on standard components like Python that are touted as delivering capabilities akin to powerhouses like Goldman Sachs (NYSE: GS) as vendors target hedge funds and banking customers.
While developers such as Numerix have been acquiring graph technology to boost their offerings, new players like Amazon Web Services (NASDAQ: AMZN) are also offering graph services. AWS unveiled its Neptune graph database in November, claiming among other things it would give developers access to more databases as new financial and other applications emerge.
Graph databases are gaining adherents for their performance querying related data. “The graph model offers an inherent indexed data structure, so it never needs to load or touch unrelated data for a given query,” Yu Xu, founder and CEO of graph database developer TigerGraph noted in a recent overview of graph technologies. “This makes it an excellent solution for better and faster real-time big data analytical queries.”
New York-based Numerix made a push into the financial sector last year with its acquisition of TFG Financial Systems, a developer of real-time risk and “position management” systems. The company said the TFG deal addresses market demand for real-time architectures that combine hybrid data management, analytics and visualization.
The March 2017 acquisition also gave Numerix a dependency graph capability. “A dependency graph is essentially a technology for connecting server systems that speak to each other in an event-driven real-time, efficient way,” said Satyam Kancharla, chief product and strategy officer at Numerix.
As electronic trading spreads to new market sectors, Numerix is betting that more customers will invest in graph database technologies. The advertised real-time intelligence capabilities could help in reacting to market shifts by calculating price and risk information.
“The structural changes stemming from post-[financial] crisis regulation have placed market participants under increasing pressure,” Bill Dwyer, vice president of business development at Numerix, noted in a blog post.
“The speed of business is accelerating as trading is moving to electronic platforms and the business is evolving to be more flow-oriented,” Dwyer added.
The company is attempting to fill a gap left by off-the-shelf systems based on middleware, then “live with other kinds of limitations,” he said.
The Numerix graph dependency layer acts like a “brain” that “dynamically orchestrates all the various nodes and the complex calculations they perform,” Dwyer explained. “The result is that calculations are performed intelligently, on an event-driven basis, and in a way that is highly efficient and highly scalable.”