Learn GREMLIN with Real Code Examples
Updated Nov 18, 2025
Explain
Gremlin focuses on traversing graph structures step-by-step using chained operations.
Powerful for multi-hop, complex, algorithmic graph traversals.
Used across many databases: JanusGraph, Cosmos DB, Neptune, OrientDB, HugeGraph, and others.
Core Features
g.V(), g.E() traversal sources
Graph mutations via addVertex/addEdge
Pattern matching with match()
Aggregations and path extraction
Shortest path, grouping, filtering
OLAP analytics via SparkGraphComputer
Basic Concepts Overview
Vertices and edges
Properties and property keys
Traversals and steps
OLTP vs OLAP modes
GraphComputer for analytics
Traversal strategies and compilers
Project Structure
Graph configuration files
Gremlin scripts
Traversal libraries/utilities
Indexes (via backend engines)
GraphComputer configs
Building Workflow
Model graph schema
Insert vertices/edges
Write traversal pipelines
Profile and optimize traversals
Deploy Gremlin Server for apps
Difficulty Use Cases
Beginner: basic traversals with g.V().has()
Intermediate: match(), group(), paths
Advanced: custom strategies, optimization
Expert: OLAP GraphComputer algorithms
Comparisons
More expressive but less intuitive than Cypher
More algorithmic than SPARQL
Database-agnostic unlike Cypher
Supports OLAP unlike many graph languages
Versioning Timeline
2009 – Gremlin introduced
2015 – TinkerPop 3 (major redesign)
2017 – Gremlin bytecode standardization
2020–2025 – Widespread adoption in cloud graph databases
Glossary
Vertex: Node in graph
Edge: Relationship between nodes
Traverser: State-carrying entity
Step: Action in traversal pipeline
GraphComputer: OLAP engine