Trekking Boldly into the Future: Going Who Knows Where in the Graph Space

Graph databases are becoming increasingly mainstream, and they offer a flexible model that can tolerate many different domains and data. The author argues that graphs are the supermodel, and any data can be modeled as a graph - whether it's documents, trees, hierarchies, or spreadsheets. Graphs already do multi-model, but in a way that's more efficient and scalable than traditional approaches. When it comes to analytics, graphs offer a natural fit for reactive and predictive analytics, using graph theory to gain insight into data. The author also discusses the trade-off between reliability and availability in distributed systems, and how Neo4j is addressing this challenge with its core-edge architecture, which includes RAFT for ensuring data safety and durability on disk.

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