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Embedded multi-model database orchestration over SQLite, DuckDB, Cypher, and exact and ANN vector search

Project description

HumemDB

Multi-model embedded data orchestration for SQL, Cypher, and vector search.

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✨ What HumemDB is

HumemDB is a Python-first embedded runtime that keeps each engine doing the job it is already good at.

  • SQLite for OLTP.
  • DuckDB for OLAP.
  • Cypher support over SQL-backed graph storage.
  • Exact and ANN vector search, with the default runtime path starting from an exact SQLite-plus-NumPy baseline today.
  • LanceDB later where the benchmark justifies an indexed ANN path.

Today, it starts as a thin Python orchestration layer over embedded engines. The longer-term goal is a single embedded system that supports standard SQL, Cypher, and vector search without forcing one engine to do every job.

The goal is not to force SQL, graph, and vector workloads through one backend just because that sounds clean. The goal is a simple, explicit orchestration layer with clear routing and defensible tradeoffs.

✅ Current status

HumemDB already ships a real v0 surface for three query modes:

  • HumemSQL v0
  • HumemCypher v0
  • HumemVector v0

Current behavior is intentionally explicit:

  • Route: sqlite or duckdb
  • Query type: sql, cypher, or vector
  • Writes go to SQLite
  • DuckDB is the analytical read path
  • Vector search starts from the exact baseline path today

🔗 Documentation

Install

HumemDB supports Python 3.10 and newer.

Install from source:

uv pip install .

Install in editable mode for development:

uv pip install -e .

For contributors, use:

uv sync

uv sync makes the local environment match the project exactly using pyproject.toml and uv.lock.

When dependencies change:

uv lock
uv sync

uv lock updates the lockfile with exact resolved versions. uv sync installs that exact environment.

Libraries HumemDB relies on

HumemDB is a pure Python orchestration layer, but it relies on a small set of core Python libraries and embedded engines:

  • sqlite3 from the Python standard library for the canonical local write path.
  • duckdb for analytical reads over the SQLite-backed source-of-truth database.
  • numpy for the exact in-memory vector search baseline.
  • sqlglot[c] for the current PostgreSQL-like SQL translation layer.
  • lancedb for benchmark work and future indexed ANN paths.
  • threadpoolctl for thread-pool coordination around compute-heavy dependencies.

Those dependencies are part of the public runtime story. HumemDB does not try to hide them behind a fake "single engine" narrative.

🧠 What is supported today

SQL

  • PostgreSQL-like portable subset translated with sqlglot
  • statement coverage: SELECT, INSERT, UPDATE, DELETE, CREATE
  • recursive CTEs intentionally unsupported in v0

Cypher

  • narrow CREATE and MATCH flows
  • labeled nodes and single directed relationships
  • relationship aliases and reverse-edge matches
  • simple WHERE ... AND ... equality filtering
  • ORDER BY and LIMIT

Vector

  • SQLite-backed vector storage
  • exact NumPy baseline path
  • bucket filtering
  • benchmark path toward indexed ANN where justified

⚡ Quick example

from humemdb import HumemDB

with HumemDB("app.sqlite3", "analytics.duckdb") as db:
    db.query(
        "CREATE TABLE users (id INTEGER PRIMARY KEY, name TEXT NOT NULL)",
        route="sqlite",
    )

    with db.transaction(route="sqlite"):
        db.query(
            "INSERT INTO users (name) VALUES (?)",
            route="sqlite",
            params=("Alice",),
        )

    result = db.query(
        "SELECT id, name FROM users",
        route="sqlite",
    )

    print(result.rows)

More examples live in examples/ and in the docs site.

🔗 Quick links

📦 Packaging

HumemDB itself is a pure Python package today. It does not ship platform-specific project binaries, even though some dependencies may install native wheels on the user side.

🗺️ Planning

Detailed internal roadmap notes now live in things-to-do.md instead of this README.

📄 License

HumemDB's own source code is licensed under MIT. See LICENSE.

Third-party dependencies keep their own licenses. Installing HumemDB may also install third-party Python packages and, in some cases, their native wheels. Those components are not relicensed under MIT just because HumemDB depends on them.

For the concrete dependency set, see pyproject.toml and uv.lock.

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