# MoteDB

> AI-native embedded multimodal database for embodied intelligence. One SQL engine natively carrying vectors, time series, full text and binary — embedded, zero-ops, MIT licensed, written in Rust. Python/Node/Rust SDKs with Arrow and pandas interop.

MoteDB stores robot data — poses, embeddings, sensor logs, binary frames — in a single embedded library with ACID transactions. Designed for power-fail-safe edge capture, single-file fleet distribution and read-only deployment. Written in Rust; runs on macOS (arm64/x64), Linux (x64/arm64) and Windows.

## Install

- [Rust — crates.io](https://crates.io/crates/motedb): `cargo add motedb`
- [Python — PyPI](https://pypi.org/project/motedb-python/): `pip install motedb-python`
- Node.js — npm: `npm install motedb`
- Source: [github.com/motedb/motedb](https://github.com/motedb/motedb)

## Core capabilities

- Vector KNN with the `<->` operator, index-accelerated (Vamana)
- Time-series semantics: TIME_BUCKET, TTL retention, LATEST BY
- Full-text search: BM25 ranking with snippet extraction
- Hybrid retrieval: BM25 × vector KNN fused with Reciprocal Rank Fusion
- BLOB columns with byte-exact equality
- MCAP (robotics capture) import
- Single-file snapshots: EXPORT DB TO 'snap.mote' — per-file CRC32, optional zstd
- Read-only containers: open_readonly(), multi-reader co-existence
- Arrow/pandas interop: query_arrow() returns pyarrow.Table (vectors as FixedSizeList<float32>)

## SQL quick example

```sql
CREATE TABLE poses (ts TIMESTAMP, sid INT, emb VECTOR(4)) TIMESERIES(ts);
SELECT ts, sid FROM poses
ORDER BY emb <-> [0.1, 0.2, 0.3, 0.4] LIMIT 5;
EXPORT DB TO 'fleet.mote';
```

## Platform matrix

macOS arm64/x64 · Linux x64/arm64 (gnu) · Windows x64 — official prebuilt binaries, smoke-tested in CI.

## License

MIT.