The Essential Criteria of Graph Databases

The Essential Criteria of Graph Databases book cover

The Essential Criteria of Graph Databases

Author(s): Sun (Author)

  • Publisher: Elsevier
  • Publication Date: 16 Jan. 2024
  • Language: English
  • Print length: 396 pages
  • ISBN-10: 0443141622
  • ISBN-13: 9780443141621

Book Description

The Essential Criteria of Graph Databases collects several truly innovative graph applications in asset-liability and liquidity risk management to spark readers’ interest and further broaden the reach and applicable domains of graph systems. Although AI has incredible potential, it has three weak links: 1. Blackbox, lack of explainability, 2. Silos, slews of siloed systems across the AI ecosystem, 3. Low-performance, as most of ML/DL based AI systems are SLOW. Hence, fixing these problems paves the road to strong and effective AI.

  • 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

Editorial Reviews

Review

Provides a detailed overview of the potential of graph computing

From the Back Cover

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.

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