The AI-native database client — graph memory + vector search + real-time sync in 5.3 MB
Project description
DriftDB Python Client
The AI-native database client. Graph memory + vector search + real-time sync in 5.3 MB.
pip install driftdb
Quick Start
from driftdb import DriftDB
db = DriftDB("http://localhost:9211", token="your-token")
# Create nodes
db.create_node(labels=["User"], properties={"name": "Amrit", "age": 25})
# Query with DriftQL
result = db.query('FIND (u:User) RETURN u.name, u.age')
# AI Memory — one line to give your LLM a brain
db.remember("User prefers dark mode")
db.remember("Meeting at 3pm tomorrow", labels=["Event"])
# Recall via vector similarity
db.recall(vector=[0.1, 0.5, 0.9], limit=5)
# Vector similarity search
db.similar([0.1, 0.5, 0.9, 0.3], threshold=0.8, limit=10)
# Statistics
db.stats()
API
| Method | Description |
|---|---|
DriftDB(url, token) |
Connect to DriftDB |
db.query(driftql) |
Execute DriftQL query |
db.create_node(labels, properties) |
Create a node |
db.get_node(id) |
Get node by ID |
db.list_nodes() |
List all nodes |
db.delete_node(id) |
Soft-delete node |
db.find(label, where_clause, returns) |
Find by label |
db.create_edge(src, tgt, type, props) |
Create edge |
db.remember(text, labels, vector) |
Store AI memory |
db.recall(text, vector, limit) |
Recall memories |
db.similar(vector, threshold, limit) |
Vector similarity |
db.backup(directory, password) |
Backup database |
db.health() / db.is_healthy() |
Health check |
db.stats() |
Database stats |
Requirements
- Python 3.8+
- A running DriftDB server (
driftdb --serve --rest)
License
SSPL-1.0 (same as MongoDB)
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