NopalDB 🌵
High-performance embedded graph database for Python, written in Rust: ACID transactions, MVCC time-travel, a Cypher-like query language (NQL), vector search, and zero-copy Apache Arrow export for ML pipelines.
Runs in-process — no server to deploy. One pip install, one file on disk.
Install
pip install nopaldb
Prebuilt wheels for Linux (x86_64/aarch64), macOS (Intel/Apple Silicon) and Windows, for CPython 3.10+ (abi3: one wheel per platform covers all versions).
Quickstart
import nopaldb
graph = nopaldb.Graph.open("./data.db")
# ACID transactions
tx = graph.begin_transaction()
alice = tx.add_node("Person", {"name": "Alice", "age": 30})
bob = tx.add_node("Person", {"name": "Bob", "age": 25})
tx.add_edge(alice, bob, "KNOWS")
tx.commit()
# Query with NQL
result = graph.execute_nql("""
find p.name, p.age
from (p:Person)
where p.age > 25
""")
for row in result:
print(f"{row['p.name']}: {row['p.age']}")
graph.close()
Isolation levels
tx = graph.begin_transaction(isolation="serializable")
# read_committed (default) | repeatable_read | serializable | read_uncommitted
Serializable transactions detect write conflicts and deadlocks; see the durability guarantees and isolation guide.
Arrow / ML pipelines
import pyarrow as pa
arrow_bytes = graph.to_arrow(label="Person")
batch = pa.ipc.open_stream(arrow_bytes).read_next_batch()
df = batch.to_pandas() # zero-copy into Pandas / Polars / PyTorch pipelines
Good to know
- One process per data directory (embedded file lock). Threads within the process run in parallel — the bindings release the GIL during database calls.
- Use
graph.bulk_loader(batch_size)for large ingestions. - Time-travel: MVCC version history is queryable; old versions are garbage collected on demand.
Links
- Repository & docs: https://github.com/sharop/nopaldb
- Adoption guide: https://github.com/sharop/nopaldb/blob/main/docs/ADOPTION.md
- NQL reference: https://github.com/sharop/nopaldb/blob/main/docs/en/NQL_REFERENCE.md
- Rust crate: https://crates.io/crates/nopaldb
License: MPL-2.0 (the nopaldb library — this repository in its entirety). The companion ecosystem apps (MCP server, NDBStudio) are AGPL-3.0-only and live in their own repositories: https://github.com/Anxious-Mind-Group/nopaldb-mcp · https://github.com/Anxious-Mind-Group/ndbstudio. Releases ≤ 0.4.31 were AGPL-3.0-only. NopalDB™ is a trademark of Sergio Haro Pérez.
1 maintainer
Metadata
1 maintainer
Release files for nopaldb 0.5.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| nopaldb-0.5.5.tar.gz | 500.8 kB | With provenance | Details |
Built distributions (wheels)
| File | Reset | |||
|---|---|---|---|---|
| nopaldb-0.5.5-cp310-abi3-win_amd64.whl | CPython 3.10 | abi3 | Windows x86-64 | Details |
| nopaldb-0.5.5-cp310-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl | CPython 3.10 | abi3 | Linux glibc 2.17+ x86-64 | Details |
| nopaldb-0.5.5-cp310-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl | CPython 3.10 | abi3 | Linux glibc 2.17+ ARM64 | Details |
| nopaldb-0.5.5-cp310-abi3-macosx_11_0_arm64.whl | CPython 3.10 | abi3 | macOS 11.0+ ARM64 | Details |
| nopaldb-0.5.5-cp310-abi3-macosx_10_12_x86_64.whl | CPython 3.10 | abi3 | macOS 10.12+ x86-64 | Details |
Total release size: 22.0 MB
Release files / nopaldb-0.5.5.tar.gz
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