Realtime over WebSocket
Durable connections. No polling or repeated API calls.
Realtime data collection,
without the operational clutter.
Keep activity organized, review the records that matter, and export them when you need them.
Example activity
Sample records14:28:01Source A{ metric: "temperature", value: 22.4 }42 B
14:28:01Source B{ action: "package_received", count: 3 }38 B
14:28:02Source A{ metric: "humidity", value: 61 }40 B
14:28:02Source C{ status: "complete", duration_ms: 184 }44 B
Built for ingestion at scale.
01 / FeaturesCSV-first storage
Compact per-day records that stay simple to export.
Verified sources
Each registered client is checked before sending activity.
Buffered writes
Batch incoming events to keep collection steady.
Live dashboard
Watch activity arrive and filter by source or content.
One-click export
Download the records you need without blocking the workflow.
Drop in the SDK. Start streaming.
02 / Python SDK# Install the client
pip install ./sdk-python
# Send an event
from datastack_sdk import DataStackClient
client = DataStackClient(
server_url="YOUR_SERVER_URL",
token="YOUR_CLIENT_TOKEN",
)
if client.connect():
client.sync({"event": "package_received"})
client.disconnect()How it works
A small client. A clear workflow.
Connect a Python source, send individual or batched events, then review and export activity from one workspace.
Ready to simplify your data workflow?
Start with the SDK guide and make the workspace your own.