What this sample helps you learn
This module demonstrates hybrid search with plain JDBC on Oracle AI Database. The sample stores product-style documents with:
What this sample demonstrates
Vector Search
Store embeddings and search records by semantic similarity.
Use when users search by meaning or AI answers need grounded records.
JSON
Document-shaped data and SQL/JSON querying inside Oracle AI Database.
Use when records need flexible structure without leaving SQL, indexes, constraints, and transactions.
Highlights
- a text content field that is embedded locally with the same MiniLM model style used in ai-vector-search
- a JSON resource file that seeds a larger sample catalog dynamically at runtime
- a VECTOR embedding column for semantic similarity
- relational columns such as category and price