Always leverage database-native data types and appropriate schema design to maximize performance and query capabilities. This includes: 1. Use database-specific type bindings when available instead of generic formats: ```typescript // Instead of: pref: JSON.stringify(this.pref) // Prefer: pref: { val: JSON.stringify(this.pref), type: oracledb.DB_TYPE_JSON } ``` 2. For vector stores or cross-platform storage, use serialization-friendly formats for complex types: ```typescript // Instead of storing Date objects directly doc.metadata.date = new Date() // Store as ISO string for better compatibility doc.metadata.date = new Date().toISOString() ``` 3. In relational databases, prefer specific typed columns over generic JSON fields for data that will be frequently filtered or sorted: ```typescript // Better schema design with specific columns for important fields await engine.pool.raw(`CREATE TABLE ${schemaName}.${tableName}( id UUID PRIMARY KEY, content TEXT NOT NULL, created_date TIMESTAMP NOT NULL, category VARCHAR(50) NOT NULL, metadata JSON // Only for truly variable/unstructured data )`); ``` This approach enables more efficient querying, better indexing capabilities, type validation at the database level, and allows you to leverage database-specific optimizations. Creating typed fields instead of dictionary-style complex types provides better type fidelity and enables richer filtering expressions like numeric/date range comparisons.