One platform for every integration
Connections, the Intuitive Pipeline Builder, scheduling, a Cloud Runtime, monitoring. All one product, so nothing falls through the gaps between tools.
One lifecycle, from first connection to production
Every workflow moves through the same five stages, in one product. No separate tools for design, scheduling and monitoring.
01
Connect
Link systems once. Credentials are stored encrypted and reused across workflows.
02
Design
Build on the canvas, or describe the outcome and let Milo draft it.
03
Test
Run on sample rows and check the output of every step before it goes live.
04
Deploy
Promote to a Cloud Runtime, on a schedule or on demand.
05
Monitor
Logs, per-node metrics and audit history for every run.
Built to run in production
Scheduling and retries
Cron schedules with built-in retries and backoff, or run on demand.
Separate environments
Promote workflows from Development to Staging to Production with controlled differences.
Encrypted connections
Credentials are stored encrypted and reused across workflows.
Monitoring and audit
Run logs, per-node metrics and audit history for every workflow.
SSO, groups and roles
Single sign-on and role-based access for teams, on the Teams plan.
Version history
Saved versions are kept, so you can see what changed and when.
Low-code, with code when you need it
Most integrations never need code. The builder handles the ordinary work: connect a system, map the fields, transform on the way through.
When a requirement goes beyond what configuration can express, add a script step to the same pipeline. Your team starts simple and adds code only where it earns its place.
Python
Transformation logic and custom processing.
JavaScript
Lightweight logic and data shaping.
SQL
Querying, staging and set-based transformation.
Normalize contact names
PYTHON runs after Map fields# Source exports put the family name in `surname`.
# Salesforce requires LastName, so fill it or reject the row.
def transform(rows, ctx):
for row in rows:
name = (row.get("surname") or row.get("LastName") or "").strip()
if not name:
ctx.reject(row, "LastName is required")
continue
row["LastName"] = name.title()
row["Email"] = (row.get("Email") or "").lower()
return rowsNo servers to run. No scripts to babysit.
We host and run your pipelines. You design the integration, we keep it running.
| Your team | DataLug | |
|---|---|---|
| Infrastructure | Nothing to provision | Hosted and maintained |
| Pipelines | Design them | Runs them |
| Scripts | Only where the logic is custom | Runs them inside the pipeline |
Decide who can change what
Decide who can see and change what. DataLug ships with role-based access, organization groups, SSO, encrypted secrets and a full audit trail on every run, so teams move fast without giving up control.
- Role-based access control across projects
- Organization groups and roles
- SSO and access controls
- Encrypted connections and secrets
- A full audit trail on every run
SSO, groups and roles on the Teams plan.
Where Salesforce migrations go wrong
Ten years of Salesforce migrations taught us where they break. Record locks. Load order. Triggers firing mid-load. Each of those has a control in the product.
Metadata discovery
Understand objects, fields and relationships before you map anything.
Error detection
See which records failed and why, during and after a load.
Record-lock control
Reduce lock contention when loading related records at volume.
Load sequencing
Parent and child records go in the right order.
Automation control
Manage triggers, flows and validation rules while a migration runs.
Build your first pipeline
Start free with Milo, for 30 days.