Emil Eifrem: As the co-founder and CEO of Neo4j, the most popular graph database, Eifrem’s insights and leadership have shaped the trajectory of graph database technology. He frequently discusses the importance of relationships in data and the potential of graph databases in various sectors.
Dr. Marko A. Rodriguez: Rodriguez, co-founder of the graph computing framework Apache TinkerPop, has been instrumental in standardizing graph database operations and analytics.
Jim Webber: As Neo4j’s Chief Scientist, Webber is deeply involved in the architecture and scaling of graph databases. His talks and writings provide deep dives into graph theory and its practical applications.
Martin Fowler: A renowned software development expert, Fowler’s contributions to the understanding and promotion of graph databases are significant. His broad perspective on software design and architecture often integrates the benefits of graph-based systems.
Dr. Michael Hunger: Leading the Developer Relations team at Neo4j, Hunger’s work spans from building the Neo4j community to developing integral parts of its software stack. His expertise bridges the gap between graph database theory and practice.
Datanaya Fidarov: An advocate for graph databases, especially in the realm of Artificial Intelligence, Fidarov’s insights into integrating graph databases with machine learning are invaluable.
Max De Marzi: As a Neo4j field engineer, De Marzi’s blog provides tutorials, case studies, and explorations into the complex problems solvable with graph databases.
Joshua Shinavier: Currently at Uber, where he works on the company’s knowledge graph, Shinavier’s perspective on large-scale, real-world applications of graph databases is enlightening.
Corey Lanum: The author of “Graph Databases in Action,” Lanum’s expertise is in graph visualization, offering a unique perspective on visually representing and understanding complex graph data.
Victor Lee: As the Director of Product Management at TigerGraph, a rising graph database, Lee’s insights into high-performance graph analytics and the future of graph databases are essential.
