Databricks to Amazon Redshift integration

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

4.8 on G2
DatabricksSource
WeldWeld
Amazon RedshiftWarehouse
Weld · New sync
DatabricksSourceDatabricksConnected
Tables to sync

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

  • Extract
  • Load
  • Keep in sync
Amazon RedshiftDestinationAmazon RedshiftReady
databricks schema
  • databricks.Synced
  • databricks.Syncing
  • databricks.Synced
  • databricks.Synced

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How it works

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

Weld · Data warehouse
Amazon RedshiftData warehouseAmazon RedshiftConnected
Data locationChosen when you connect
CredentialsService account or key, stored encrypted
Use cases

Why sync Databricks to Amazon Redshift?
Ready for analysis.

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

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

  • Centralized data warehouse

    Bring Databricks data into Amazon Redshift 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 Databricks to Amazon Redshift. Connect BI tools like Looker, Metabase, or Power BI.

Data

What data can you sync?
From Databricks to Amazon Redshift.

Weld syncs the objects the Databricks connector exposes into Amazon Redshift, 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 Amazon Redshift for you.

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

    Claude CodeOpus 5
    >

    Which Databricks tables do we have in Amazon Redshift, and which is the largest?

    Looking up what Weld has synced from Databricks.

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

    Technical considerations.
    What to expect.

    Incremental syncing
    Weld uses incremental syncing where supported by the Databricks API, loading only new and updated records to minimize data transfer and warehouse costs.
    Schema handling
    Weld automatically manages schema changes. If Databricks adds new fields, they're detected and added to the corresponding Amazon Redshift 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.
    FAQ

    Common questions.
    About Databricks to Amazon Redshift.

    Start syncing Databricks to Amazon Redshift.

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

    DatabricksSource
    WeldWeld
    Amazon RedshiftWarehouse