Published: 24 January 2019
Summary
Graph data stores can efficiently model, explore and query data with complex interrelationships across data silos, but there is a lot of hype around them. This research provides technical professionals dealing with data and analytics an overview of graph database use cases and their architecture.
Included in Full Research
- What Is a Graph Data Store?
- Relational Data Stores Are Not Sufficient for Highly Interconnected Data
- Key Value or Other NoSQL Data Stores Are Not Sufficient
- Why Graph Data Stores?
- Strengths
- Weaknesses
- Different Types of Modeling Graphs
- Property Graphs
- RDFs
- Hypergraphs
- Use Cases
- Graph Data Store Standards
- Graph Data Store Architecture
- Graph Storage
- Graph Processing
- Graph Data Query Languages
- How Graph Data Stores Handle Transactions, High Availability (HA) and Large-Scale Graphs
- Matrix of Graph Data Stores and Their Features