Discourse to Snowflake integration

Connect Discourse to Snowflake and automatically sync your customer support data. Weld extracts data from Discourse, loads it into Snowflake, and lets you transform the data using SQL or dbt, no custom scripts required.

4.8 on G2
DiscourseSource
WeldWeld
SnowflakeWarehouse
Weld · New sync
DiscourseSourceDiscourseConnected
Tables to sync

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

  • Extract
  • Load
  • Keep in sync
SnowflakeDestinationSnowflakeReady
discourse schema
  • discourse.Synced
  • discourse.Syncing
  • discourse.Synced
  • discourse.Synced

Trusted by data and AI teams

  • Flatpay
  • Holafly
  • eComplete
  • Dishoom
  • Danish Endurance
  • Female Invest
  • Son of a Tailor
  • Onomondo
  • Medik8
  • Pas Normal Studios
How it works

How to set up Discourse to Snowflake in Weld.
In the app, with the API or an agent.

Weld · New Discourse sync
DiscourseNew connectionDiscourseAuthorised
Connection namediscourse
AuthorizeOpens Discourse to grant read access
Use cases

Why sync Discourse to Snowflake?
Ready for analysis.

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

Build reliable dashboards and reports by querying Discourse data directly in Snowflake using SQL or your preferred BI tool.

  • Support metrics and SLA tracking

    Monitor ticket volume, resolution times, and satisfaction scores from Discourse in Snowflake. Correlate support data with product and customer data.

  • Centralized data warehouse

    Bring Discourse data into Snowflake 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 Discourse to Snowflake. Connect BI tools like Looker, Metabase, or Power BI.

Data

What data can you sync?
From Discourse to Snowflake.

Weld syncs the objects the Discourse connector exposes into Snowflake, 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 Snowflake for you.

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

    Claude CodeOpus 5
    >

    Which Discourse tables do we have in Snowflake, and which is the largest?

    Looking up what Weld has synced from Discourse.

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

    Technical considerations.
    What to expect.

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

    Start syncing Discourse to Snowflake.

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

    DiscourseSource
    WeldWeld
    SnowflakeWarehouse