Struct DbVectorStore 

pub struct DbVectorStore { /* private fields */ }

Database-backed in-process vector store.

Stores vectors as BLOBs in SQLite and performs cosine similarity in memory. For production-scale workloads, prefer the Qdrant-backed store.

Implementations

impl DbVectorStore

pub fn new(pool: DbPool) -> Self

Create a new DbVectorStore from an existing connection pool.

The pool must come from a database that has run the zeph-db migrations (which create the vector_store table).

Trait Implementations

impl VectorStore for DbVectorStore

fn ensure_collection( &self, collection: &str, _vector_size: u64, ) -> Pin<Box<dyn Future<Output = Result<(), VectorStoreError>> + Send + '_>>

Create a collection with cosine-distance vectors of vector_size dimensions.

fn collection_exists( &self, collection: &str, ) -> Pin<Box<dyn Future<Output = Result<bool, VectorStoreError>> + Send + '_>>

Returns true if collection exists in the backend.

fn delete_collection( &self, collection: &str, ) -> Pin<Box<dyn Future<Output = Result<(), VectorStoreError>> + Send + '_>>

Delete a collection and all its points.

fn upsert( &self, collection: &str, points: Vec<VectorPoint>, ) -> Pin<Box<dyn Future<Output = Result<(), VectorStoreError>> + Send + '_>>

Upsert points into collection.

fn search( &self, collection: &str, vector: Vec<f32>, limit: u64, filter: Option<VectorFilter>, ) -> Pin<Box<dyn Future<Output = Result<Vec<ScoredVectorPoint>, VectorStoreError>> + Send + '_>>

Search collection for the limit nearest neighbours of vector.

fn delete_by_ids( &self, collection: &str, ids: Vec<String>, ) -> Pin<Box<dyn Future<Output = Result<(), VectorStoreError>> + Send + '_>>

Delete specific points from collection by their string IDs.

fn scroll_all( &self, collection: &str, key_field: &str, ) -> Pin<Box<dyn Future<Output = Result<ScrollResult, VectorStoreError>> + Send + '_>>

Scroll (paginate) all points in collection and return a map of point_id → { key_field → value } payload entries.

fn health_check( &self, ) -> Pin<Box<dyn Future<Output = Result<bool, VectorStoreError>> + Send + '_>>

Return true if the backend is reachable and operational.

fn create_keyword_indexes( &self, _collection: &str, _fields: &[&str], ) -> Pin<Box<dyn Future<Output = Result<(), VectorStoreError>> + Send + '_>>

Create keyword payload indexes for the given field names.