DatriseAI-first ETL

Source connector

CallRail connector

CallRail integration for databases, warehouses and BI tools

Call tracking and marketing attribution. Datrise captures CallRail entities such as calls, trackers, form submissions, sources, call outcomes and recordings, then lands normalized and typed models for warehouse reporting, attribution, and AI workflows.

Of the 6 objects, 4 sync as upserts keyed on the primary key and 2 as append-only streams, so each incremental run moves only what changed since the last watermark. Every object lands in its own table (for example `callrail_calls`) with a schema derived from the CallRail API rather than a flattened CSV, in any of the 43 supported destinations.

Datrise is in early access: pick a destination below to open the CallRail pipeline page, and join the waitlist to get the CallRail connector with guided onboarding.

Incremental syncSchema-aware mapping43 destinations available

What CallRail data Datrise extracts

Each object lands in its own typed table. Sync mode is derived from the object: history-style objects append, everything else upserts.

ObjectLanding tableSync mode
callscallrail_callsAppend-only, incremental by timestamp
trackerscallrail_trackersUpsert by primary key, incremental on updated-at
form submissionscallrail_form_submissionsUpsert by primary key, incremental on updated-at
sourcescallrail_sourcesUpsert by primary key, incremental on updated-at
call outcomescallrail_call_outcomesAppend-only, incremental by timestamp
recordingscallrail_recordingsUpsert by primary key, incremental on updated-at

Popular destinations for CallRail

Choose a destination below to open the ready pipeline page.

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    Airtable

    Relational spreadsheet destination for ops and go-to-market teams.

    View pipeline
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    Amazon Athena

    Serverless SQL over S3 data lake tables.

    View pipeline
  • A
    Amazon DynamoDB

    Serverless key-value and document store on AWS.

    View pipeline
  • A
    Amazon QuickSight

    AWS serverless BI with SPICE and embedded analytics.

    View pipeline
  • A
    Amazon Redshift

    AWS petabyte-scale warehouse with Spectrum.

    View pipeline
  • A
    Amazon S3 Data Lake

    Object storage landing zone for parquet and snapshots.

    View pipeline
  • A
    Apache Superset

    Open-source BI for SQL exploration, charts, and dashboard publishing.

    View pipeline
  • A
    Azure Data Lake Storage

    ADLS Gen2 object storage for analytics workloads.

    View pipeline
  • A
    Azure Synapse

    Microsoft analytics workspace with SQL pools.

    View pipeline

CallRail connector FAQ

What CallRail data does the connector extract?
6 objects: calls, trackers, form submissions, sources, call outcomes and recordings. Each lands in its own table with types preserved; history-style objects (2: calls and call outcomes) load as append-only streams.
Is the CallRail integration incremental?
Yes. After the initial full load, every run reads only records changed since the last watermark (updated-at or event timestamp) and applies an upsert or an append depending on the object.
Where can I load CallRail data?
Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each CallRail → destination pair has its own page with the object-to-table mapping.

Related sources

Other sources in the same category, each with its own connector page.

Early access

Launch your CallRail pipeline with guided onboarding

Join the waitlist to get priority access for CallRail integrations with guided setup, schema-aware mapping, and production-grade incremental sync.