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The Essential Criteria of Graph Databases

 
Publisher: Elsevier
Date of Publication:
 
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EUR 130.00
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Long 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
Table of Contents:
1. The history of graph computing and graph databases2. The fundamentals and principles of graph database3. Graph database architectural design4. Graph algorithms5. Scalable graph database6. The world powered by graph technology (or: graph database use cases)7. Planning, benchmarking, and optimization of graph systems