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About this event
Sayari is in the counterparty and supply chain risk intelligence industry. The Sayari platform, built on Memgraph, provides global visibility into the relationships between businesses and entities, helping them uncover risks in universal beneficial ownership within corporate and supply chain trade networks.
Sayari has built a global knowledge graph of corporate ownership and supply chains - with nearly 2 billion nodes and 7 billion edges.
To enable users to run efficient traversals over this graph, Sayari experimented with several different graph databases before settling on Memgraph. In the process, Sayari identified some essential lessons on how to efficiently store large graphs in memory, how to scale live analytic queries over millions of nodes, and how to model complex, real-world problems like beneficial ownership and international supply chain networks.
Ultimately, Sayari ended up with a setup that combines an OLTP database's low latency with an OLAP database's processing scalability. In effect, Sayari uses Memgraph as a stand-alone graph analytics engine for their 2 billion-node knowledge graph.
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James leads Product and Engineering at Sayari, a company analyzing corporate ownership, supply chains, and risk to combat sanctions evasions, money laundering, and other forms of financial crime. He has extensive experience working with a number of different graph databases, most recently Memgraph. He is the lead contributor to the network visualization library Trellis. In a previous life he designed maps.
Memgraph is a dynamic, lightweight graph database optimized for analyzing data, relationships, and dependencies quickly and efficiently. It offers a rich suite of pre-built deep path traversal algorithms and a library of traditional, dynamic, and ML algorithms tailored for advanced graph analysis.
