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Graph Database: Introduction

Graph Database: Introduction

Part of: Graph Database User Guide

What is a Graph Database?

A graph database is a specialized database designed to store and query data represented as graphs. Unlike traditional relational databases that use tables, graph databases use:

  • Nodes (Vertices): Entities in your data (e.g., Person, Product, Location)
  • Edges (Relationships): Connections between entities (e.g., FRIEND_OF, PURCHASED, LOCATED_IN)
  • Properties: Key-value pairs attached to nodes and edges

Graph databases excel at:

  • Finding patterns and relationships in connected data
  • Traversing complex relationships efficiently
  • Discovering communities and clusters
  • Path-finding and network analysis

Why HeliosDB Graph Database?

HeliosDB provides a high-performance, Neo4j-compatible graph database with unique advantages:

Performance

  • <78ms P99 latency for 6-degree traversals on 1M node graphs
  • 450K vertices/second insertion rate
  • 400ns neighbor lookup latency
  • 9.6GB memory footprint for 100M edges

Scalability

  • Supports 1 billion+ edges
  • Native sharding and distribution
  • Parallel traversal algorithms
  • Memory-mapped storage for large graphs

Integration

  • Unified SQL and graph queries - Query graphs from SQL
  • ACID transactions with snapshot isolation
  • Multi-model database - Combine relational, document, time-series, and graph
  • Standard APIs - Bolt protocol, REST, GraphQL

Neo4j Compatibility

  • Cypher query language support
  • Bolt protocol compatibility (use Neo4j drivers)
  • Migration tools for easy transition
  • Similar semantics for pattern matching and traversal

Cost Efficiency

  • 10x lower TCO - No separate graph database needed
  • Unified infrastructure - One database for all workloads
  • Open source - No licensing fees

Version: 6.5 Last Updated: November 17, 2025