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MotherDuck target connectorDbDeux supports MotherDuck

Every operational system you run, landed in MotherDuck.

DLH.io syncs your POS, payroll, HRIS, ERP, and SaaS data straight into your own MotherDuck account — then DbDeux gives your analytics engineers an AI-native dbt IDE to model it, test it, and ship it. Serverless DuckDB analytics, no clusters to size, no idle compute.

  • 100+ source connectors
  • Slimmer CI 4–8× faster than dbt Cloud
  • Access-token auth & column hashing
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The DLH.io + MotherDuck stack

Three jobs, one platform, your warehouse

Ingestion, transformation, and analysis all run against the MotherDuck account you own.

Ingestion

Get operational data into MotherDuck without building pipelines

DLH.io Sync Bridges replicate your POS, payroll, HRIS, ERP, and SaaS systems into your MotherDuck database on the schedule you set. No-code setup, schema-aware, and fully managed — so your team is querying data on day one instead of maintaining connectors.

Browse connectors
  • 100+ pre-built connectors, including Toast, Aloha, Dayforce, ADP, NetSuite, and Salesforce
  • Incremental and delta loads, historical re-loads, and captured deletes
  • Column selection and column hashing before data ever lands
  • Priority scheduling and API-initiated Sync Bridge runs
Reference architecture

Your data never leaves your MotherDuck account

DLH.io writes into the MotherDuck database you designate. Transformation runs on your MotherDuck compute, under your access tokens — DLH.io orchestrates, MotherDuck stores and executes.

Your source systems

POS, payroll, HRIS, ERP, CRM, databases, APIs

  • Toast
  • Aloha
  • Dayforce
  • ADP
  • NetSuite
  • Salesforce
  • SQL Server

DLH.io Sync Bridge

Managed, schema-aware replication on your schedule

  • Incremental loads
  • Column hashing
  • Captured deletes
  • Audit tables

DbDeux on MotherDuck

dbt models compiled to DuckDB SQL

  • Slimmer CI
  • Atlas Catalog
  • Atlas Metrics
  • Lineage & ERD

Your consumption layer

BI, notebooks, apps, and AI — all on governed models

  • Dashboards
  • Local DuckDB
  • Python notebooks
  • Data apps
MotherDuck

Stages 2 through 4 execute against your MotherDuck account. Storage, compute, access tokens, and retention stay under your control and your MotherDuck plan.

Why MotherDuck

A warehouse sized to the data you actually have

MotherDuck pairs DuckDB's speed with a serverless cloud service. Pair it with DLH.io and the teams who need operational reporting get a complete stack — ingestion, modeling, and analysis — without the overhead of a large cloud warehouse.

Right-sized for operational data

Restaurant, retail, payroll, and ERP datasets rarely need a big-data warehouse. MotherDuck's serverless DuckDB engine handles them fast, without clusters to size or idle compute to pay for.

Local and cloud, same tables

Analysts can query the data DLH.io lands from the MotherDuck UI or from DuckDB on their own machine, so exploration doesn't wait on a shared warehouse queue.

Connected in an afternoon

Create a landing database, generate a MotherDuck access token, and paste it into the DLH.io target form. Most teams land their first source the same day.

Security & governance

Built for the team that has to approve it

Payroll and HR data carries the strictest handling requirements in the business. These are the controls your security reviewer will ask about.

Access-token authentication

DLH.io connects with a MotherDuck access token you generate and own. Revoke or rotate it in MotherDuck on the cadence your security policy requires.

A dedicated landing database

Land DLH.io data in its own MotherDuck database — we recommend DLH.io_RAW — so raw replicated data stays separate from your modeled and shared datasets.

Column hashing and selection

Hash or exclude sensitive columns before they are written, so PII from payroll and HR sources never lands in raw form.

Network controls

Grantlist DLH.io's published IP ranges for any cloud vendor or network access your MotherDuck setup requires.

Audit tables and run logs

Every Sync Bridge run writes audit records and a step-level log, so you can reconcile what changed and when.

Captured deletes and re-syncs

Deleted source rows are captured on all supported tables, and any table can be flagged to reload its full history on the next Sync Bridge run.

FAQ

Questions we get from MotherDuck teams

See your own data in MotherDuck

Bring one source system to a 30-minute session and we will show you the Sync Bridge, the landed tables, and the DbDeux models running on your MotherDuck database.

Not on MotherDuck yet? Create a MotherDuck account and we will help you connect it.