libs-data-persistence

You can implement vector search by storing vector embeddings and performing similarity searches across your data. This enables semantic search capabilities directly within your data persistence layer for advanced retrieval.

Yes, multi-backend file storage supports persisting data locally or in cloud storage including S3 and Supabase. This provides flexible storage options depending on your scalability and infrastructure requirements.

Building searchable indexes uses efficient JSONL-backed indexes for quick data retrieval and filtering. This approach structures your data to enable fast querying across large datasets without complex database setups.

Managing typed resources with authorization policies involves defining structured data with built-in access controls. This ensures only authorized users can access sensitive information based on their actor permissions.

Yes, knowledge graph support includes storing and querying RDF triples for relationship-based data. This enables complex relationship mapping and graph-based querying alongside traditional file and index storage.

Typed resource authorization ensures only authorized users can access sensitive information when storing user profiles and application logs. It provides built-in access control policies to secure structured data across your application.