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HTTP File to Databricks integration

Connect HTTP File to Databricks and automatically sync your file storage data. Weld extracts data from HTTP File, loads it into Databricks, and lets you transform the data using SQL or dbt, no custom scripts required.

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4.8 on G2
HTTP FileSource
WeldWeld
DatabricksWarehouse
Weld · New sync
HTTP FileSourceHTTP FileConnected
Tables to sync

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

  • Extract
  • Load
  • Keep in sync
DatabricksDestinationDatabricksReady
http_file schema
  • http_file.Synced
  • http_file.Syncing
  • http_file.Synced
  • http_file.Synced

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How it works

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

Setup guideAPI guideMCP docs
Weld · New HTTP File sync
HTTP FileNew connectionHTTP FileAuthorised
Connection namehttp_file
AuthorizeOpens HTTP File to grant read access
Use cases

Why sync HTTP File to Databricks?
Ready for analysis.

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

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

  • Centralized data warehouse

    Bring HTTP File data into Databricks 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 HTTP File to Databricks. Connect BI tools like Looker, Metabase, or Power BI.

Data

What data can you sync?
From HTTP File to Databricks.

Weld syncs the objects the HTTP File connector exposes into Databricks, 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 Databricks for you.

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

    Set up the MCP serverClaudeCursorChatGPTGemini
    Claude CodeOpus 5
    >

    Which HTTP File tables do we have in Databricks, and which is the largest?

    Looking up what Weld has synced from HTTP File.

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

    Technical considerations.
    What to expect.

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

    HTTP File setup guide

    How to connect HTTP File to Weld, step by step.

    Documentation

    Databricks setup guide

    How to connect Databricks to Weld, step by step.

    Connector

    HTTP File connector

    Everything Weld does with HTTP File.

    Connector

    Databricks connector

    Everything Weld does with Databricks.

    FAQ

    Common questions.
    About HTTP File to Databricks.

    Start syncing HTTP File to Databricks.

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

    HTTP FileSource
    WeldWeld
    DatabricksWarehouse
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    Related

    Related integrations.
    More with HTTP File and Databricks.

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