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What is a Graph Database?

Graph databases store data in the form of nodes, using flexible graphical representation to manage data. Multidimensional in nature, graph databases use nodes that contain lists of relationships between different data.

Components of graph databases, including nodes, properties, and edges.

When to use a graph database

  • When you want to solve many-to-many relationship problems.
  • When you need to generate insight from the existing data and not just manage larger volumes of data.
  • When the relationships between data elements are important.
  • When your application needs  low latency with large-scale datasets.

Use cases for graph databases

  • Social networks, logistics, and spatial data.
  • Fraud detection and analytics.
  • Product-recommendation engines.
  • Identity and access management.


The RedisGraph module offers a fast and efficient way to manage and process graph data. It offers fast graph processing powered by linear algebra and matrix multiplication. RedisGraph is based on a unique approach and architecture that allows use cases like social graph operation, fraud detection, and real-time recommendation to be executed 10x – 600x faster than any other graph database.

Next section  ►  Search-engine databases