Alopex Family
Asopitech Labo
Enterprise plans
Use case
Alopex ships Python wheels with every release (officially supported). Use SQL, vector search, and graph straight from Python, with no separate infrastructure to stand up — and scale from a single embedded instance to a production cluster on the same data file.
Install
pip install alopexThe alopex package — both the Database and DataFrame APIs.
Use it from Python
import alopex
db = alopex.Database.open("./my_data")
results = db.execute_sql(
"SELECT * FROM docs WHERE category = ?",
["science"],
)
similar = db.search_hnsw("docs", query_embedding, k=10)The same data file, seamlessly from embedded to server to distributed cluster.
VECTOR type, HNSW, and vector_similarity() built into SQL.
Full SQL, plus a Polars-style lazy DataFrame API.
Runs embedded, scales out when you need it — no second infrastructure.
Database
Same data file from embedded to cluster. Raft-based KVS + SQL + Vector + Graph ETL in one engine.
AI / RAG
Microsoft GraphRAG for AWS (Bedrock + Anthropic)
Database
Day-0 speed, all the way to scale. The startup pitch for Alopex DB: grow from MVP to cluster on the same data file.