PuppyGraph Blog

Explore what an RDF Knowledge Graph is, how it structures data using triples, and why it’s essential for the Semantic Web. Learn key use cases, tools, and real-world RDF graph examples.

Discover 7 real-world knowledge graph examples—from Google and LinkedIn to Amazon and Wikidata. Learn how these systems organize data, improve search, and power AI insights.

Compare TigerGraph and Neo4j on speed, clustering, schema design, and query languages to choose the right graph database for your use case.

External Attack Surface Management (EASM) helps organizations discover, monitor, and secure all internet-facing assets. Learn how EASM improves visibility, reduces cyber risks, and strengthens your overall security posture.

Compare TigerGraph and Dgraph on speed, scalability, and graph database features. See key strengths, tradeoffs, and understand the best fit for your project.

Discover what a dynamic graph is, how it models evolving relationships over time, and its key types, algorithms, visualization methods, and real-world applications in AI, cybersecurity, and data analytics.

Learn how Text to Cypher converts natural language into Cypher queries for Neo4j and other graph databases. Explore examples, tools, and use cases driving AI-powered query generation.

Microsoft OneLake comes provisioned with every Microsoft Fabric tenant as the default data lake. As the “OneDrive of data”, OneLake provides a single logical lake that unifies storage across workspaces and engines. This allows teams to spend less time managing overlapping storage resources and more time collaborating on a shared, governed lake.

Learn how Attack Surface Management helps identify, monitor, and secure your digital assets to reduce cyber risks and prevent breaches.

Compare ArangoDB and JanusGraph to understand their architectures, performance, scalability, and graph database features. Learn which one fits your project needs best.

Discover how an Asset Graph connects and visualizes relationships between digital assets, helping organizations enhance visibility, reduce risk, and improve security posture.

Explore how graph-based anomaly detection works, including nodes, edges and subgraph anomalies, methods using graph neural networks, and real-world applications in security, finance and networks.

Learn what an acquaintance graph is, how it models relationships between entities, and its use in social networks, AI, and graph databases. Explore structure, examples, and benefits.

Compare Apache Iceberg vs Delta Lake to understand their features, performance, ecosystem support, and use cases. Learn which open table format is best for your data lakehouse.

See how PuppyGraph adds graph queries to ClickHouse, enabling real-time relationship analysis for cybersecurity data without moving or copying data.