Learn GREMLIN with Real Code Examples

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.

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

Vertices and edges

Properties and property keys

Traversals and steps

OLTP vs OLAP modes

GraphComputer for analytics

Traversal strategies and compilers

Graph configuration files

Gremlin scripts

Traversal libraries/utilities

Indexes (via backend engines)

GraphComputer configs

Model graph schema

Insert vertices/edges

Write traversal pipelines

Profile and optimize traversals

Deploy Gremlin Server for apps

Beginner: basic traversals with g.V().has()

Intermediate: match(), group(), paths

Advanced: custom strategies, optimization

Expert: OLAP GraphComputer algorithms

More expressive but less intuitive than Cypher

More algorithmic than SPARQL

Database-agnostic unlike Cypher

Supports OLAP unlike many graph languages

2009 – Gremlin introduced

2015 – TinkerPop 3 (major redesign)

2017 – Gremlin bytecode standardization

2020–2025 – Widespread adoption in cloud graph databases

Vertex: Node in graph

Edge: Relationship between nodes

Traverser: State-carrying entity

Step: Action in traversal pipeline

GraphComputer: OLAP engine