VantaDB × Haystack

Haystack DocumentStore adapter for VantaDB.

Install

Not on PyPI yet. The vantadb-haystack package declares Alpha status and will go live with the first adapters-v* tag release (no local dist/ built yet). Until then, install from source.

# Today, from a repo checkout
cd integrations/haystack && pip install .

Install from PyPI (after first release)

pip install vantadb-haystack

Quickstart

from vantadb_haystack import VantaDBDocumentStore

store = VantaDBDocumentStore(db_path="./my_data")

# Write documents
store.write_documents([
    {"id": "1", "content": "VantaDB is an embedded vector database written in Rust.",
     "meta": {"source": "docs"}},
])

# Filter documents
results = store.filter_documents(filters={"source": "docs"})
for doc in results:
    print(doc.content)

API

• write_documents(documents, policy) — store documents
• filter_documents(filters) — retrieve by filter
• delete_documents(filters) — remove documents
• count_documents(filters) — count documents

Why VantaDB?

• Embedded & local-first: the storage engine is a Rust library embedded in your process — no server to deploy, no network hop; data lives in your filesystem.
• Persistent hybrid search: vectors + BM25 text search out of the box, where Haystack's InMemoryDocumentStore covers only small single-process cases.
• Zero-setup alternative to hosted stacks: unlike Zep (requires a server) or Cognee (spins up its own knowledge-graph runtime), VantaDB is a plain library you import.

Development

pip install -e .