Reference SurrealQL syntax, operators, and functions for SurrealDB queries.
npx skills add https://github.com/baladithyab/engram --skill surrealql-reference
Please help me install this Agent Skill. Skill: surrealql-reference Source: https://github.com/baladithyab/engram/tree/main/skills/surrealql-reference Command: npx skills add https://github.com/baladithyab/engram --skill surrealql-reference
This Skill provides a comprehensive reference for SurrealQL syntax, helping developers write correct and efficient queries, especially when dealing with SurrealDB's unique features that differ from standard SQL.
DEFINE TABLE and DEFINE FIELD syntax required.Use the surrealql-reference skill to find the correct syntax for defining a full-text search index in SurrealQL.
High-intent search queries and answers about installing and using this skill.
To define a full-text search index in SurrealQL, use the DEFINE INDEX statement with the BM25 indexing strategy on your target table fields. This enables efficient text matching and retrieval for your SurrealDB records.
SurrealQL differs from standard SQL by introducing graph traversal, record links, and specific full-text search operators. It extends traditional SQL with unique statements like RELATE for managing graph relationships directly within the database.
To create graph relationships in SurrealDB, use the SurrealQL RELATE statement to connect record IDs. This allows you to define directed edges between nodes for efficient graph traversal queries.
Use the SurrealQL UPSERT statement when you need to update an existing record or create a new one if it does not exist, preventing duplicate key errors. Use CREATE when you specifically want to insert new records only.
Yes, you can define schema field types and table definitions in SurrealDB using the DEFINE TABLE and DEFINE FIELD statements. This allows strict schema enforcement and specifies data types for your database records.
To optimize SurrealQL queries for vector search, use the HNSW indexing strategy when defining your index. This hierarchical navigable small world approach ensures fast approximate nearest neighbor lookups for high-dimensional data.
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