PuppyGraph Blog

Learn the Cypher Programming Language, the declarative graph query language used in Neo4j and beyond. Explore syntax, examples, use cases, and how Cypher powers graph data modeling and applications.

Discover how Continuous Threat Exposure Management (CTEM) helps organizations identify, prioritize, and reduce cyber risks through real-time visibility and proactive security validation.

Compare Memgraph vs Neo4j to understand differences in performance, scalability, and use cases. Find out which graph database best fits your needs.

Learn how Cloud Security Posture Management (CSPM) helps organizations detect misconfigurations, ensure compliance, and strengthen multi-cloud security.

Discover how Application Security Posture Management (ASPM) enhances AppSec by unifying risk detection, prioritization, and remediation across the software lifecycle.

Explore AWS Neptune vs Neo4j to see how they stack up in pricing, scalability, and graph query support. Learn which graph database is right for your project.

Discover how graph databases help detect fraud in banking, fintech, and e-commerce by uncovering hidden relationships, spotting fraud rings, and reducing false positives with real-time analytics.

Learn what Entity Resolution is, how it works, and why it’s essential for data quality. Explore methods, tools, and use cases in MDM, customer 360, fraud detection, and more.

Compare Apache Hudi vs Apache Iceberg to explore their key features, performance, use cases, and ecosystem support. Learn which table format is right for your data lakehouse.

Discover how LLM graph databases integrate large language models with graph technology to improve reasoning, semantic search, and knowledge management for AI-driven applications.

Discover how the MCP Knowledge Graph connects data, relationships, and context to deliver a unified view for smarter decision-making. Learn its features, use cases, benefits, and implementation roadmap.

Dgraph vs Neo4j compared: discover key differences in features, performance, and deployment. See which graph database is the best choice for your workload.

Learn how Apache Iceberg and Trino work together to power modern data lakehouses. Explore features, architecture, use cases, and optimization for scalable analytics.

Learn how SQL Graph brings graph database capabilities to relational systems. Discover how to model, query, and analyze relationships using nodes, edges, and the MATCH syntax in SQL Server.

Explore the differences between a knowledge graph and a graph database, their unique use cases, benefits, and how to fit them into your data strategy.