Intro -- The Essential Criteria of Graph Databases -- Copyright -- Contents -- Chapter 1: History of graph computing and graph databases -- 1.1. What exactly is a graph? -- 1.1.1. The forgotten art of graph thinking, part I -- 1.1.2. The forgotten art of graph thinking II -- 1.1.3. A brief history of graph technology development -- 1.2. The evolution of big data and database technologies -- 1.2.1. From data to big data to deep data -- 1.2.2. Relational database vs graph database -- 1.3. Graph computing in the Internet of things (IoT) era -- 1.3.1. Unprecedented capabilities
1.3.2. Differences between graph computing and graph database -- Chapter 2: Graph database basics and principles -- 2.1. Graph computing -- 2.1.1. Basic concepts of graph computing -- 2.1.2. Applicable scenarios of graph computing -- 2.2. Graph storage -- 2.2.1. Basic concepts of graph storage -- 2.2.2. Graph storage data structure and modeling -- 2.3. Evolution of graph query language -- 2.3.1. Basic concepts of database query language -- 2.3.2. Graph query language -- Chapter 3: Graph database architecture design -- 3.1. High-performance graph storage architecture
3.1.1. Key features of high-performance storage systems -- 3.1.2. High-performance storage architecture design ideas -- 3.2. High-performance graph computing architecture -- 3.2.1. Real-time graph computing system architecture -- 3.2.2. Graph database schema and data model -- 3.2.3. How the core engine handles different data types -- 3.2.4. Data structure in graph computing engine -- 3.2.5. How to partition (shard) a large graph -- 3.2.6. High availability and scalability -- 3.2.7. Failure and recovery -- 3.3. Graph query and analysis framework design
