SKIP

Generic Description

Discard the first N rows after ordering.

Simple example:

MATCH (p:Person) RETURN p.name ORDER BY p.name SKIP 10

Consumer-Level Explanation

Use SKIP when the query must discard the first N rows after ordering and the planner needs to see that operation as part of the Cypher row pipeline. Keep the clause explicit because it controls row grain, variable scope, and what later clauses are allowed to reference.

More Detailed Explanation

SKIP is the offset side of offset-limit pagination. It is simple and familiar, but its real cost profile depends on how much data the system must still scan and sort before it can skip.

What this clause is really for:

it defines one concrete stage in the Cypher row pipeline, so variables available before and after SKIP must be clear
it should make graph structure, temporal filters, document payload shaping, or procedure output explicit instead of relying on client-side interpretation
planner tooling depends on this clause boundary to know row grain, variable scope, and whether later expressions are reads, writes, schema operations, or projections

Advanced Example

This example keeps SKIP inside a complete query pipeline so the clause boundary, visible variables, and returned row shape are clear to planner tooling.

MATCH (u:User)-[e:VIEWED]->(d:Document)
TIME e.ts BETWEEN datetime('2025-01-01T00:00:00Z') AND datetime('2025-02-01T00:00:00Z')
WITH u, d, date_trunc('day', e.ts) AS day_bucket,
     unpivot(properties(d.metadata)) AS metadata_rows,
     cosine_similarity(vector(properties(d).embedding), vector([0.22, 0.18, 0.44])) AS score
RETURN u.user_id, d.title, day_bucket, metadata_rows, score
ORDER BY day_bucket DESC, score DESC
SKIP 20
LIMIT 10

Real Use Cases

offset paging over stable sorted reports
jumping into ranked result sets for review

Real Limitations And Tradeoffs

large offsets are usually a bad fit for high-scale APIs
requires deterministic ordering to be meaningful
can encourage inefficient pagination patterns if used blindly