Jaz Ku

Solution Architect

Jaz Ku is a Solution Architect with a background in Computer Science and an interest in technical writing. She earned her Bachelor's degree from the University of San Francisco, where she did research involving Rust’s compiler infrastructure. Jaz enjoys the challenge of explaining complex ideas in a clear and straightforward way.

Blog

  • Cybersecurity

    Software Dependency Graphs: Definition, Use Cases, and Implementation

    Explore what software dependency graphs are, how they model relationships in code, and how tools like PuppyGraph help manage complexity and optimize builds.

    Jaz Ku

  • AI/ML LLM

    Text-to-SQL LLM: A Practical Guide

    Learn how LLM-powered Text-to-SQL works, its benefits, challenges, and use cases. Discover how AI converts plain English into accurate SQL queries.

    Jaz Ku

  • Query your table as a graph.Petabytes. Subsecond. No data movement.

    Free downloadBook demo

  • Graph Data Model

    What Is a Compliance Graph? Visualizing Risk & Regulation

    Learn how compliance graphs connect regulations, policies, and risks to automate compliance, boost visibility, and simplify audits for modern enterprises.

    Jaz Ku

  • Graph Database

    Top 7 ArangoDB Alternatives of 2026

    Explore the best ArangoDB alternatives for graph database solutions. Compare performance, scalability, and features of seven top tools to find your ideal match.

    Jaz Ku

  • Graph Algorithm

    What is Breadth-First Search?

    Learn how the Breadth-First Search algorithm works in graph traversal, including BFS steps, implementation, complexity analysis, and common real-world applications.

    Jaz Ku

  • Graph Database

    Graph Database for Fraud Detection: Prevent Fraud

    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.

    Jaz Ku

  • Data Modeling

    Many-to-Many Relationship: Explained

    Learn many-to-many relationships with simple real-life and database examples. Understand how entities connect and why this model is important.

    Jaz Ku

  • Data Lakehouse

    Apache Hudi vs. Iceberg: Key Differences Explained

    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.

    Jaz Ku

  • Graph Database

    Top 4 Cassandra Alternatives of 2026

    Explore the top alternatives to Apache Cassandra, including scalable NoSQL and distributed databases like MongoDB, ScyllaDB, Amazon DynamoDB, and more. Compare features, performance, and use cases.

    Jaz Ku

  • Database Concept

    What Is Disk Database?

    A disk database stores data on persistent storage to ensure durability and scale. Learn how disk-based databases work, benefits, and use cases.

    Jaz Ku

  • Graph Database

    What is a Customer 360 Graph Database?

    Learn how a graph database powers a true Customer 360 view by connecting data across silos. Discover use cases, architecture, and top tools for customer intelligence.

    Jaz Ku

  • AI/ML

    What Is Agent Observability? How Does It Work?

    Learn what agent observability is, how to implement it with logs, metrics, and traces, and how to evaluate LLM agent outcomes across tools, retrieval, and multi-agent workflows. Query telemetry as a graph with PuppyGraph.

    Jaz Ku

  • Data Lakehouse

    Iceberg vs Delta Lake: Key Differences Explained

    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.

    Jaz Ku

  • Data Modeling

    What is Compliance Analytics? Benefits and Challenges

    Compliance analytics uses data and automation to monitor, measure, and improve regulatory compliance. Learn benefits, use cases, and best practices.

    Jaz Ku

  • Cybersecurity

    What is Continuous Threat Exposure Management?

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

    Jaz Ku

  • Graph Analysis

    Graph Analytics in Big Data: Concepts and Examples

    Discover how graph analytics in big data reveals hidden patterns, relationships, and insights. Learn key use cases, tools, and real-world applications for enterprise-scale decision-making.

    Jaz Ku

  • Data Modeling

    Top 7 Root Cause Analysis Tools

    Discover the 7 best root cause analysis (RCA) tools to identify, analyze, and resolve issues effectively. Compare features and use cases to find the right fit.

    Jaz Ku

  • Cybersecurity

    Attack Surface Management: Complete 2026 Guide

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

    Jaz Ku

  • Data Lakehouse

    Apache Iceberg Trino: Modern Data Lakehouse Explained

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

    Jaz Ku

  • Graph Database

    Node Count vs Edge Count: Key Graph Database Metrics

    Learn the difference between node count and edge count in graph databases. Understand their impact on performance, scalability, and data modeling best practices.

    Jaz Ku

  • Cybersecurity

    What is Cloud SIEM?

    Explore what Cloud SIEM is, how it enhances cybersecurity, its core components, and best practices for implementing a secure and scalable SIEM solution in the cloud. See how PuppyGraph adds graph analytics to uncover deeper insights and improve threat detection.

    Jaz Ku

  • Cybersecurity

    What is Exposure Management?

    Learn how exposure management helps organizations identify, prioritize, and mitigate cyber risks. Improve resilience with continuous monitoring and proactive defense.

    Jaz Ku

  • Knowledge Graph Graph RAG

    Knowledge Graph vs RAG: Know the Differences

    Compare knowledge graphs with Retrieval-Augmented Generation (RAG). Learn how both approaches enhance AI accuracy, retrieval quality, and context understanding.

    Jaz Ku

  • Knowledge Graph

    Knowledge Graph vs Vector Database: Key Differences

    Compare Knowledge Graphs and Vector Databases to understand their strengths, use cases, and key differences. Learn which technology fits semantic search, AI applications, and enterprise data integration.

    Jaz Ku

  • Graph Database

    JanusGraph vs Dgraph: Which Graph Database Fits Your Workload

    Compare JanusGraph and Dgraph on data models, Gremlin vs DQL/GraphQL, storage architecture, indexing, consistency, clustering, and traversal speed for production graphs.

    Jaz Ku

  • Graph Database

    JanusGraph vs Amazon Neptune: Key Differences & Comparisons

    Compare JanusGraph and Amazon Neptune on architecture, indexing, consistency, clustering, and traversal performance for graph applications.

    Jaz Ku

  • Graph Data Model

    Nodes and Edges in Graph Theory

    Understand the fundamentals of nodes and edges in graph theory. Learn how graphs represent relationships, their types, real-world applications, and how to build them using modern graph tools.

    Jaz Ku

  • Cybersecurity

    What Is External Attack Surface Management?

    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.

    Jaz Ku

  • Announcement

    Graph Analytics on Microsoft OneLake: Zero ETL with PuppyGraph

    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.

    Jaz Ku & Sa Wang

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$ docker run -p 8081:8081 \
  -p 8182:8182 -p 7687:7687 \
  puppygraph/puppygraph:latestPulling puppygraph/puppygraph:latestStarting PuppyGraphWeb console listening on 0.0.0.0:8081Gremlin endpoint listening on 0.0.0.0:8182PuppyGraph is running# no pipelines · no second database · no data movement