SurrealQL Performance

Techniques for making SurrealDB queries fast: structuring record IDs and keys for data locality, choosing and verifying the right indexes, and precomputing values with computed fields and views instead of recomputing them on every read.

Target the latest stable SurrealDB release. Confirm version-sensitive syntax (record ranges, COMPUTED fields, FULLTEXT index options) against https://surrealdb.com/docs, and validate examples with surreal validate. See the surrealql skill for version detection.

When to use this skill

• A query is slow or scans more records than expected
• Designing record IDs to support efficient lookups and range scans
• Choosing between standard, UNIQUE, full-text SEARCH, or vector indexes
• Confirming whether an index is actually used (EXPLAIN)
• Deciding whether to store a derived value vs. compute it on read

Topic map

Top rules

• Design IDs for access patterns. Record IDs are stored in sorted order. Put the most selective, range-friendly component first (e.g. weather:['London', d'2025-02-13T05:00Z']) so related records sit together and range queries avoid full-table scans. See references/keys.md.
• Prefer record ranges over WHERE on the ID. SELECT * FROM person:1..1000 uses key ordering directly; filtering with WHERE after a full scan does not.
• Index the fields you filter, sort, or join on — but no more. Every index adds write cost. Order composite index fields from most to least selective and to match your query's filter/sort order. See references/indexing.md.
• Verify, don't assume. Run EXPLAIN (or EXPLAIN FULL) to confirm a query uses the index you expect before concluding it is optimized.
• Precompute expensive, read-heavy values. Use computed fields, a DEFINE TABLE ... AS SELECT view, or a DEFINE EVENT to maintain derived data rather than recomputing aggregates on every query. See references/computed-fields.md.
• Use bound parameters. Parameterized queries are safer and let the engine reuse query plans.