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Memgraph at Scale: Analyzing Company Ownership & Supply Networks With a 2 Billion-Node Graph

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.

What you will learn:
  • How to efficiently store large graphs in memory
  • How live analytical queries are unique to Memgraph
  • How Sayari uses Memgraph’s hybrid in-memory architecture
  • Why Sayari chose Memgraph over other graph databases
“With 40 million new entities and 50 million new connections being added into Sayari platforms each month, no other graph database is able to handle the performance needs like Memgraph does”
William Hurley, Director of Infrastructure, Sayari
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