Optimize SurrealDB performance through record ID and key design, indexing strategy, and computed/derived fields. Use when queries are slow, when designing record IDs for locality and range scans, choosing between standard/unique/full-text/vector indexes, verifying index usage with EXPLAIN, or deciding whether to precompute values with computed fields, views, or events. Triggers: slow query, performance, record id design, range scan, DEFINE INDEX, EXPLAIN, computed field, FUTURE, DEFINE TABLE AS…
Optimize SurrealDB performance through record ID and key design, indexing strategy, and computed/derived fields.
Use when queries are slow, when designing record IDs for locality and range scans, choosing between standard/unique/full-text/vector indexes, verifying index usage with EXPLAIN, or deciding whether to precompute values with computed fields, views, or events.
Triggers: slow query, performance, record id design, range scan, DEFINE INDEX, EXPLAIN, computed field, FUTURE, DEFINE TABLE AS SELECT.
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surrealdb
version
0.1.0
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skill mdSKILL.md3,164 B
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SKILL.md
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
Topic
Reference
Record ID & key structuring for locality and range scans
[references/keys.md](references/keys.md)
Index types, composite order, verifying usage, rebuild cost
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](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](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](references/computed-fields.md).
Use bound parameters. Parameterized queries are safer and let the engine
