Advanced data modeling: Using user-defined types and Protocol Buffers for Amazon Keyspaces

This article demonstrates how to model complex data in Amazon Keyspaces using user-defined types (UDTs) and Protocol Buffers, comparing their strengths and use cases for a real estate property management system.

• User-defined types (UDTs) provide native CQL integration with server-side schema validation and field-level querying capabilities
• UDTs support up to eight nesting levels, 256 per region, and 50 per table with a 25 KB schema size limit
• Protocol Buffers offer schema evolution, compact binary serialization, and cross-language compatibility stored as BLOB fields
• UDTs require the frozen keyword for nested UDTs and collections but don't support ALTER TYPE after creation
• Protobuf provides forward/backward compatibility and decoupled application schemas but lacks server-side validation and requires full-object reads for updates
• Choose UDTs for stable schemas with field-level queries; choose Protobuf for evolving schemas and multi-store portability

Amazon Keyspaces supports both approaches for modeling complex data, enabling developers to select the best solution based on schema stability, query patterns, and evolution requirements.