PostgreSQL + pgvector implementation of VectorStore.
Uses pgvector extension for efficient vector similarity search with support for IVFFlat and HNSW indexes.
Features:
- Hardware-accelerated vector operations
- HNSW indexing for fast approximate nearest neighbor search
- Connection pooling via HikariCP
- ACID transactions
- Scalable to millions of vectors
Requirements:
- PostgreSQL 12+ with pgvector extension
- Run: CREATE EXTENSION IF NOT EXISTS vector;
Value parameters
- dataSource
-
HikariCP connection pool
- tableName
-
Name of the vectors table
Attributes
- Companion
- object
- Graph
-
- Supertypes
Members list
Value members
Concrete methods
Clear all records from the store.
Clear all records from the store.
Attributes
- Returns
-
Success or error
- Definition Classes
Close the store and release resources.
Count total records in the store.
Count total records in the store.
Value parameters
- filter
-
Optional metadata filter
Attributes
- Returns
-
Record count
- Definition Classes
Create HNSW index for faster similarity search. Call this after bulk loading data for best performance.
Create HNSW index for faster similarity search. Call this after bulk loading data for best performance.
Value parameters
- efConstruction
-
Size of dynamic candidate list (default 64)
- m
-
Maximum number of connections per layer (default 16)
Attributes
Delete a record by its ID.
Delete a record by its ID.
Value parameters
- id
-
The record identifier
Attributes
- Returns
-
Success or error
- Definition Classes
Delete multiple records by their IDs.
Delete multiple records by their IDs.
Value parameters
- ids
-
The record identifiers
Attributes
- Returns
-
Success or error
- Definition Classes
Delete all records matching a metadata filter.
Delete all records matching a metadata filter.
Value parameters
- filter
-
The metadata filter
Attributes
- Returns
-
Number of records deleted
- Definition Classes
Delete all records with IDs starting with the given prefix.
Delete all records with IDs starting with the given prefix.
Value parameters
- prefix
-
The ID prefix to match
Attributes
- Returns
-
Number of records deleted
- Definition Classes
Retrieve a record by its ID.
Retrieve a record by its ID.
Value parameters
- id
-
The record identifier
Attributes
- Returns
-
The record if found
- Definition Classes
Retrieve multiple records by their IDs.
Retrieve multiple records by their IDs.
Value parameters
- ids
-
The record identifiers
Attributes
- Returns
-
The found records (missing IDs are silently skipped)
- Definition Classes
List records with pagination.
List records with pagination.
Value parameters
- filter
-
Optional metadata filter
- limit
-
Maximum records to return
- offset
-
Number of records to skip
Attributes
- Returns
-
Records in insertion order
- Definition Classes
Search for similar vectors using cosine similarity.
Search for similar vectors using cosine similarity.
Value parameters
- filter
-
Optional metadata filter
- queryVector
-
The query embedding
- topK
-
Number of results to return
Attributes
- Returns
-
Matching records with similarity scores
- Definition Classes
Get statistics about the vector store.
Get statistics about the vector store.
Attributes
- Returns
-
Store statistics
- Definition Classes
Store a vector record.
Store a vector record.
If a record with the same ID exists, it will be replaced.
Value parameters
- record
-
The record to store
Attributes
- Returns
-
Success or error
- Definition Classes
Store multiple vector records in a batch.
Store multiple vector records in a batch.
More efficient than individual upserts for bulk operations.
Value parameters
- records
-
The records to store
Attributes
- Returns
-
Success or error
- Definition Classes