The Essential Criteria Of Graph Databases
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The Essential Criteria of Graph Databases
Although AI has incredible potential, it has three weak links: 1. Blackbox, lack of explainability2. Silos, slews of siloed systems across the AI ecosystem3. Low-performance, most of ML/DL based AI systems are SLOW.Fixing these problems will pave the road to strong and effective AI. Graph databases, particularly high-performance graph database or graph computing, should allow this to happen.The Essential Criteria of Graph Databases simply broadens the horizon of graph applications. The book collects several truly innovative graph applications in asset-liability and liquidity risk management, which hopefully will spark readers' interest in further broaden the reach and applicable domains of graph systems. - Presents updates on the essential criteria of graph database(s) and how they are quite different from traditional relational database or other types of NoSQL DBMS or any of those big-data frameworks (i.e., Hadoop, Spark, etc.) - Clearly points out the key criteria that readers should pay attention to - Teaches users how to avoid common mistakes and how to get hands-on with system architecture design, benchmarking or selection of an appropriate graph platform/vendor-system
Getting Started with the Graph Query Language (GQL)
Learn how to build and query graph databases with this first comprehensive guide to ISO-standard GQL featuring 50+ hands-on examples and a real-world case study that will change the way you work with connected data Key Features Go beyond theory and apply key concepts and syntax through interactive tutorials and practical examples via the GQL Playground Leverage advanced features of GQL to manipulate graph data efficiently Explore GQL applications in data analytics and discover how to leverage graph knowledge in real-world scenarios Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGraph Query Language is becoming the go-to standard for graph databases, especially with its support for interconnected analytics and GenAI capabilities. This book comes from a team of industry veterans who know exactly how to break down the fundamental GQL concepts, graph terms, definitions, catalog systems, and everything that matters in actual work. You’ll get to grips with graph data types, value expressions, graph matching patterns, and modifying statements through practical GQL examples. With access to the GQL Playground via Ultipa Graph, you’ll get hands-on experience querying and manipulating graph data. Once you've got the basics down, you’ll tackle advanced GQL topics such as path modes, complex path matching patterns, shortest path queries, composite statements, session and transaction commands, and procedures. You’ll also learn to create extensions and understand the design of graph databases to solve industry issues. The authors cover techniques like property graphs to help you optimize your graph queries and offer insights into the future of GQL and graph technology. By the end of this book, you’ll confidently query and update graph data, run graph algorithms, and create visualizations. Plus, you’ll apply your learnings to a real-world use case of money flow analysis for assessing bank client behaviors and detecting transaction risks.What you will learn Experiment with GQL syntax on GQL Playground, including MATCH, RETURN, INSERT, UPDATE, and DELETE Work with operators, functions, and variables in an organized fashion Become familiar with complex topics such as varying path matching modes, repeated variables, shortest path, procedures, and transactions Enhance execution speed through indexing or caching systems Understand how to manage access control effectively Tackle real-world issues with a case study focused on money transaction analytics Who this book is for This book is for graph database developers, DBAs, programmers, data engineers, and analysts who want to learn the new graph database standard GQL. A basic understanding of graph and relational databases, data models, knowledge of SQL basics, and programming will make the content easy to grasp. While it is designed to be accessible even if you don’t have a background in graph theory, familiarity with concepts like nodes, edges, relationships, and the distinction between directed and undirected graphs will enhance your learning experience.
Graph Databases
Author: Ian Robinson
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2015-06-10
Discover how graph databases can help you manage and query highly connected data. With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems. This second edition includes new code samples and diagrams, using the latest Neo4j syntax, as well as information on new functionality. Learn how different organizations are using graph databases to outperform their competitors. With this book’s data modeling, query, and code examples, you’ll quickly be able to implement your own solution. Model data with the Cypher query language and property graph model Learn best practices and common pitfalls when modeling with graphs Plan and implement a graph database solution in test-driven fashion Explore real-world examples to learn how and why organizations use a graph database Understand common patterns and components of graph database architecture Use analytical techniques and algorithms to mine graph database information