Full-Text Search Meets the Graph: Apache Lucene Inside Neo4j

We have documents that need full-text search, but those documents also have meaningful relationships. Do we split search and graph traversal across two systems or keep them together? Most developers reach for Elasticsearch or a dedicated search service when they need full-text search. It's a reasonable reaction, but it introduces an extra service to operate, an extra data pipeline to maintain, and an extra hop in every query. What's easy to miss is that Neo4j ships with Apache Lucene built in — the same underlying search library on which Elasticsearch is built — and when our data are already in a graph, adding full-text search on top is a single Cypher command!

More importantly, full-text search in Neo4j can do something a standalone search engine can't: it serves as an entry point into the graph. We can find our initial results with Lucene, then traverse relationships to discover what surrounds them. That two-phase pattern — search-then-traverse — is what this article describes.