The company said its contribution is expected to make “it easier to bring graph algorithms to bear, dramatically broadening how they reveal connections in their data.

Graph data science is when you want to answer questions, not just with your data, but with the connections between your data points — that’s the 30-second explanation, according to Alicia Frame.

It also compresses data up to 10 times. TigerGraph also supports different graph partitioning algorithms enabling it to split very large graphs over a distributed architecture.

In recent years, the Massively Parallel Computation (MPC) model has gained significant attention. However, most of distributed and parallel graph algorithms in the MPC model are designed for ...

Dr. Alin Deutsch of UC San Diego explains in a Q&A why graph database algorithms will become the driving force behind the next generation of AI and machine learning apps.