Merkle Science leverages TigerGraph’s terabyte-level production graph database with blockchain

Merkle Science, a predictive blockchain monitoring and investigative platform, will use TigerGraph’s advanced graph analytics to preempt and prevent financial crime. Merkle Science, with TigerGraph, will enhance how the company helps its customers, which include government agencies and financial institutions, stay one step ahead of criminals. This will be done via the construction of a cryptocurrency network graph using TigerGraph, giving Merkle Science the ability to analyse over 2.5 TB of data in real time, delving five to 10 hops into the data to better connect relationships that they were not able to do prior to unlock deeper, wider and operational analytics at scale.

“Blockchain is still considered a nascent technology that is changing at a rapid pace. We are excited to partner with TigerGraph for their ability to analyze and visualize tremendous amounts of graph data. TigerGraph’s ability to handle large quantities of data coupled with their elegant and powerful query language GSQL have enabled us to build a graph data-warehouse which we use to help our users understand flows of funds and determine their risk exposure. TigerGraph has proven to be invaluable in helping our users to differentiate between good actors and bad ones,” said Nirmal Aryath Koroth, Co-founder and Chief Technology Officer at Merkle Science.

As cryptocurrency and blockchain increasingly become more mainstream, the ecosystem that surrounds and supports it will also develop rapidly, while increasing the prevalence of it being a target for financial crime. As such, risk management is key – from government institutions to financial institutions across derivatives, credit, insurance and more. As such, the cryptocurrency network graph that Merkle Science has constructed using TigerGraph enables their customers to run queries identifying the percentage of funds sent or received from different types of actors (such as Darknet, Exchanges, Scams and Smart Contracts) from a specific location or address, which is hugely advantageous in detecting and analysing potential criminal activity.

Merkle Science’s cryptocurrency network graph, which currently contains over 2.5 TB of data and consists of 5 billion vertices and 36 billion edges, supports a complete extract, transfer and load (ETL) each day that takes under an hour, with near-instant streaming updates. “We reached out to TigerGraph as we’ve been trying to find an elegant way to visualize our investigative data over the last two years. Other incumbents in the graph database space weren’t able to process our vast amounts of data fast enough in order to generate graphs in real time. TigerGraph helped solve that issue for us – with its ETL ingestion speed, we could do both batch and streaming load at the same time. TigerGraph’s GSQL software program is also the most sophisticated query language I’ve seen so far and it’s flexibility allows us to implement complex graph algorithms which would otherwise be impossible or take far longer to implement on other incumbents,” added Aryath Koroth.

TigerGraph is the only graph database capable of providing real-time deep link analytics across multiple nodes or hops for massive datasets, making it the perfect foundation for building a company to do blockchain analytics, in order to help all of their customers scale.

“Merkle Science’s teaming with TigerGraph further validates our strength in the blockchain and financial services fraud detection and prevention sector,” said Joseph Lee, Vice President of Asia Pacific & Japan at TigerGraph. “Powered by TigerGraph’s advanced graph analytics, meaningful data insights with real-world implications can be delivered to give Merkle Science an edge over their competition while providing their customers with immediate and preemptive detection of criminal activity – and with significant time and cost savings. As we continue our expansion across APAC, we look forward to unleashing data’s true potential to help more customers drive business growth, make better decisions and achieve tangible benefits.”