Full-Text and Vector Search in Neo4j
Go beyond exact-match lookups by adding full-text and vector indexes to Neo4j, enabling fuzzy text search and semantic similarity queries that extend the database for modern search and AI workloads.
Why Search Indexes Matter
Plain property lookups in Neo4j are great for exact matches, but real applications need more. Users misspell words, search across multiple fields, and increasingly expect semantic results.
Neo4j extends its capabilities with two specialized index types:
- Full-text indexes for fuzzy, multi-field text search
- Vector indexes for similarity search over embeddings
Both are first-class features you can manage with Cypher.
Creating a Full-Text Index
A full-text index is built over one or more node labels and properties. Once created, it powers tokenized, case-insensitive search.
The example creates an index named movieSearch over the title and plot properties of Movie nodes.
CREATE FULLTEXT INDEX movieSearch
FOR (m:Movie)
ON EACH [m.title, m.plot];All lessons in this course
- Stored Procedures and UDFs
- Integrating with BI and Visualization Tools
- Advanced Data Ingestion Pipelines
- Full-Text and Vector Search in Neo4j