DatriseAI-first ETL

Source connector

Apify connector

Apify integration for databases, warehouses and BI tools

Web scraping and browser automation platform. Datrise captures Apify entities such as actors, runs, datasets, key-value stores, request queues and run logs, 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 `apify_actors`) with a schema derived from the Apify 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 Apify pipeline page, and join the waitlist to get the Apify connector with guided onboarding.

Incremental syncSchema-aware mapping43 destinations available

What Apify 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
actorsapify_actorsUpsert by primary key, incremental on updated-at
runsapify_runsAppend-only, incremental by timestamp
datasetsapify_datasetsUpsert by primary key, incremental on updated-at
key-value storesapify_key_value_storesUpsert by primary key, incremental on updated-at
request queuesapify_request_queuesUpsert by primary key, incremental on updated-at
run logsapify_run_logsAppend-only, incremental by timestamp

Popular destinations for Apify

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

Apify connector FAQ

What Apify data does the connector extract?
6 objects: actors, runs, datasets, key-value stores, request queues and run logs. Each lands in its own table with types preserved; history-style objects (2: runs and run logs) load as append-only streams.
Is the Apify 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 Apify data?
Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each Apify → 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 Apify pipeline with guided onboarding

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