DatriseAI-first ETL

Source connector

Freshcaller connector

Freshcaller integration for databases, warehouses and BI tools

Cloud call center for support and sales. Datrise captures Freshcaller entities such as calls, agents, queues, phone numbers, call metrics 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 `freshcaller_calls`) with a schema derived from the Freshcaller 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 Freshcaller pipeline page, and join the waitlist to get the Freshcaller connector with guided onboarding.

Incremental syncSchema-aware mapping43 destinations available

What Freshcaller 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
callsfreshcaller_callsAppend-only, incremental by timestamp
agentsfreshcaller_agentsUpsert by primary key, incremental on updated-at
queuesfreshcaller_queuesUpsert by primary key, incremental on updated-at
phone numbersfreshcaller_phone_numbersUpsert by primary key, incremental on updated-at
call metricsfreshcaller_call_metricsAppend-only, incremental by timestamp
recordingsfreshcaller_recordingsUpsert by primary key, incremental on updated-at

Popular destinations for Freshcaller

Choose a destination below to open the ready pipeline page.

  • A
    Airtable

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

    View pipeline
  • A
    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

Freshcaller connector FAQ

What Freshcaller data does the connector extract?
6 objects: calls, agents, queues, phone numbers, call metrics and recordings. Each lands in its own table with types preserved; history-style objects (2: calls and call metrics) load as append-only streams.
Is the Freshcaller 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 Freshcaller data?
Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each Freshcaller → 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 Freshcaller pipeline with guided onboarding

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