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Amazon S3 to MotherDuck integration

Connect Amazon S3 to MotherDuck and automatically sync your cloud data warehouse data. Weld extracts data from Amazon S3, loads it into MotherDuck, and lets you transform the data using SQL or dbt, no custom scripts required.

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4.8 on G2
Amazon S3Source
WeldWeld
MotherDuckWarehouse
Weld · New sync
Amazon S3SourceAmazon S3Connected
Tables to sync

Your own tables, picked when you set up the sync.

  • Extract
  • Load
  • Keep in sync
MotherDuckDestinationMotherDuckReady
aws_s3 schema
  • aws_s3.Synced
  • aws_s3.Syncing
  • aws_s3.Synced
  • aws_s3.Synced

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How it works

How to set up Amazon S3 to MotherDuck in Weld.
In the app, with the API or an agent.

Setup guideAPI guideMCP docs
Weld · New Amazon S3 sync
Amazon S3New connectionAmazon S3Authorised
Connection nameaws_s3
AuthorizeOpens Amazon S3 to grant read access
Use cases

Why sync Amazon S3 to MotherDuck?
Ready for analysis.

Centralizing your Amazon S3 data in MotherDuck lets you join it with other data sources for cross-platform analytics and deeper insights.

Build reliable dashboards and reports by querying Amazon S3 data directly in MotherDuck using SQL or your preferred BI tool.

  • Centralized data warehouse

    Bring Amazon S3 data into MotherDuck alongside other sources to create a single source of truth for your organization.

  • Automated reporting

    Replace manual exports and spreadsheet-based reporting with automated pipelines from Amazon S3 to MotherDuck. Connect BI tools like Looker, Metabase, or Power BI.

Data

What data can you sync?
From Amazon S3 to MotherDuck.

Weld syncs the objects the Amazon S3 connector exposes into MotherDuck, and you choose which tables and fields to include. The connector's docs list what is available.

    Weld MCP server

    Ask your agent.
    It queries MotherDuck for you.

    Connect Claude, Cursor, ChatGPT or your own agent to Weld over MCP. It reads the Amazon S3 context, finds the tables it needs and runs the query in MotherDuck.

    Set up the MCP serverClaudeCursorChatGPTGemini
    Claude CodeOpus 5
    >

    Which Amazon S3 tables do we have in MotherDuck, and which is the largest?

    Looking up what Weld has synced from Amazon S3.

    ●weld·search_available_references
    ⎿raw.aws_s3.*
    tables, columns and freshness
    ●weld·get_reference_schema
    ⎿columns, types and nullability
    ●weld·run_query
    ⎿select count(*) from {{raw.aws_s3.…}}
    submitted
    ●weld·get_query_status
    ⎿DONE
    ●weld·get_query_result
    ⎿rows returned
    ✓Answered from Amazon S3 data in MotherDuck
    >Ask about your Amazon S3 data
    Under the hood

    Technical considerations.
    What to expect.

    Incremental syncing
    Weld uses incremental syncing where supported by the Amazon S3 API, loading only new and updated records to minimize data transfer and warehouse costs.
    Schema handling
    Weld automatically manages schema changes. If Amazon S3 adds new fields, they're detected and added to the corresponding MotherDuck tables.
    Data freshness
    Sync frequency depends on your Weld plan. Most connectors support schedules from every 5 minutes up to daily intervals.
    Security
    All data is encrypted in transit (TLS) and at rest. Weld is SOC 2 Type II compliant and supports IP whitelisting for database connections.
    Resources

    Keep reading.
    Guides, docs and schema.

    Documentation

    Amazon S3 setup guide

    How to connect Amazon S3 to Weld, step by step.

    Documentation

    MotherDuck setup guide

    How to connect MotherDuck to Weld, step by step.

    Connector

    Amazon S3 connector

    Everything Weld does with Amazon S3.

    Connector

    MotherDuck connector

    Everything Weld does with MotherDuck.

    FAQ

    Common questions.
    About Amazon S3 to MotherDuck.

    Start syncing Amazon S3 to MotherDuck.

    Set up your Amazon S3 data pipeline in minutes. No credit card required. Free for 14 days.

    Amazon S3Source
    WeldWeld
    MotherDuckWarehouse
    Start for freeTalk to us
    Related

    Related integrations.
    More with Amazon S3 and MotherDuck.

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