DatriseAI-first ETL

Source connector

Harvest Forecast connector

Harvest Forecast integration for databases, warehouses and BI tools

Resource scheduling and project capacity planning. Datrise captures Harvest Forecast entities such as assignments, people, projects, clients, milestones and scheduled hours, then lands normalized and typed models for warehouse reporting, attribution, and AI workflows.

Of the 6 objects, 6 sync as upserts keyed on the primary key and 0 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 `harvest_forecast_assignments`) with a schema derived from the Harvest Forecast 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 Harvest Forecast pipeline page, and join the waitlist to get the Harvest Forecast connector with guided onboarding.

Incremental syncSchema-aware mapping43 destinations available

What Harvest Forecast 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
assignmentsharvest_forecast_assignmentsUpsert by primary key, incremental on updated-at
peopleharvest_forecast_peopleUpsert by primary key, incremental on updated-at
projectsharvest_forecast_projectsUpsert by primary key, incremental on updated-at
clientsharvest_forecast_clientsUpsert by primary key, incremental on updated-at
milestonesharvest_forecast_milestonesUpsert by primary key, incremental on updated-at
scheduled hoursharvest_forecast_scheduled_hoursUpsert by primary key, incremental on updated-at

Popular destinations for Harvest Forecast

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
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    Amazon S3 Data Lake

    Object storage landing zone for parquet and snapshots.

    View pipeline
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    Apache Superset

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

    View pipeline
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    Azure Data Lake Storage

    ADLS Gen2 object storage for analytics workloads.

    View pipeline
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    Azure Synapse

    Microsoft analytics workspace with SQL pools.

    View pipeline

Harvest Forecast connector FAQ

What Harvest Forecast data does the connector extract?
6 objects: assignments, people, projects, clients, milestones and scheduled hours. Each lands in its own table with types preserved; history-style objects (0) load as append-only streams.
Is the Harvest Forecast 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 Harvest Forecast data?
Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each Harvest Forecast → 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 Harvest Forecast pipeline with guided onboarding

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