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Getting Started with DataLug

Foundations

DataLug is an AI-native Integration Platform as a Service (iPaaS). It connects applications, databases, APIs and cloud platforms through visual data pipelines. You design flows on a canvas, configure connections to your systems, and the DataLug runtime executes them on a schedule or on demand.

Is DataLug for me?

DataLug fits teams that move data between systems on a recurring basis (CRM and warehouse, ERP and analytics, file drops and database loads) and want to build those flows visually instead of maintaining custom scripts. It is designed for data, operations and integration engineers who need repeatable, observable data pipelines.

What you do on the platform​

  • Connect to source and target systems (Snowflake, PostgreSQL, Salesforce, S3, SFTP, Generic API and others).
  • Design a flow on the visual canvas: Source, Transform, Load, with optional branching, looping and notifications.
  • Test the flow against real data with Quick Debug Run (10 rows).
  • Deploy the flow as a Job with a schedule and an environment.
  • Monitor runs from the Runtime Executions page with per-node logs, row counts and payload samples.
  • Ask Milo, the built-in AI assistant, to draft a data pipeline, write a query or explain a failed run. See Milo in the app.

Where to start​

  1. Quickstart
    Build and run your first data pipeline in about ten minutes. Open Quickstart.
  2. Core concepts
    Learn the vocabulary: account, project, data pipeline, connection, action, environment, runtime. Open Core concepts.
  3. Your first data pipeline
    A guided PostgreSQL to Snowflake walkthrough you can adapt to your own systems. Open the walkthrough.
  4. Browse the catalog
    Connectors for databases, file storage, CRM, ticketing, chat, email, spreadsheets, log destinations and any HTTP API, and nodes for sources, transforms, control flow and output. Start from Connectors or Nodes.

Free 30-day trial​

A Free account is a 30-day trial. It includes job scheduling, version history and the AI Builder. It does not include SAML single sign-on, log streaming, GitHub backup or organization groups.

Volume is capped at 2 connectors and 25,000 records per run, on a single environment and a Shared Cloud Agent. A run that reads more than 25,000 source rows stops with a plan message. When the trial ends, sign-in opens the Trial Ended page. Your data is kept. See Trial ended.

Where each part of the docs lives​

  • App pages describe each page of the app (Dashboard, Projects, Connections and others) under App pages.
  • Nodes is the reference for every node type under Nodes.
  • Connectors is the reference for every system DataLug connects to under Connectors.
  • Guides walk through common tasks under Guides.
  • FAQ answers common questions at FAQ.