RocketRide Vector

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A RocketRide-managed vector store backed by PostgreSQL + pgvector in your own provisioned RocketRide cloud database — with zero database setup and a real vector index from the first write.

What it does

Mirrors the generic vectordb_postgres store node: accepts documents (with embeddings from a bound vectorizer) on the documents lane, upserts them into a pgvector table, and serves keyword and semantic search on the questions lane.

Two differences from the generic node:

1. No connection fields. Instead of host/user/password, the node resolves a ready per-tenant DSN from the account layer (Account.resolve_db_dsn(client_id)), keyed by the authenticated connection identity. Requires signing into RocketRide cloud; on the open-source build without a cloud identity the node fails at start with RocketRide cloud DB nodes require signing into RocketRide cloud.
2. Default HNSW index. The generic node creates no index, so every semantic search is a sequential scan. This node creates an HNSW index over the embedding column when the table is first created. The operator class is derived from the similarity config so Postgres actually uses the index (cosine → vector_cosine_ops, l2 → vector_l2_ops, inner_product → vector_ip_ops), with build parameters m = 16, ef_construction = 64 (overridable). pgvector's HNSW supports at most 2000 dimensions; for wider vectors the index is skipped with a warning and search falls back to a sequential scan.

There is no direct-execute path — vector stores are structured (search/upsert), and raw SQL over the vector tables is covered by rocketride_sql (same tenant database).

Embeddings come from the separate vectorizer binding — not in-node.

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Configuration

Lanes

Lane in	Lane out	Description
documents	(none)	Upsert document chunks into the vector table
questions	documents	Keyword / semantic search, results emitted as documents

Fields

Field	Type	Description
collection	string	Default "rocketride". Name of the table to store vectors
score	number	Default 0.5. Minimum similarity score for a document to be returned
similarity	string	Default "cosine". One of cosine, l2, inner_product. Also selects the HNSW index operator class
hnsw_m	integer	Default 16. HNSW graph degree used when the index is first created
hnsw_ef_construction	integer	Default 64. HNSW build-time candidate list size used when the index is first created

There are intentionally no host / port / user / password / database fields — the connection is resolved from your signed-in RocketRide identity. The vector dimension is not configured; it is derived from the first document's embedding at write time.

Schema

Field	Type	Description	Default
rrvector.collection	string	Table Name of the table to store vectors in your RocketRide cloud database.	"rocketride"
rrvector.hnsw_ef_construction	integer	HNSW ef_construction HNSW build-time candidate list size used when the index is first created.	64
rrvector.hnsw_m	integer	HNSW m HNSW graph degree (max connections per layer) used when the index is first created.	16
rrvector.profile	string	RocketRide cloud database Connect to...	"cloud"
rrvector.provider	string		const: "rocketride_vector"
rrvector.score	number	Score threshold Minimum similarity score for a document to be returned by search.	0.5
rrvector.similarity	string	Similarity Metric The similarity metric to use for vector search. Also selects the HNSW index operator class.	"cosine"

Dependencies

• psycopg2-binary
• pgvector