DatriseAI-first ETL

Source connector

Contentful connector

Contentful integration for databases, warehouses and BI tools

Headless CMS for structured content delivery. Datrise captures Contentful entities such as entries, content types, assets, spaces, locales and publish events, then lands normalized and typed models for warehouse reporting, attribution, and AI workflows.

Of the 6 objects, 5 sync as upserts keyed on the primary key and 1 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 `contentful_entries`) with a schema derived from the Contentful 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 Contentful pipeline page, and join the waitlist to get the Contentful connector with guided onboarding.

Incremental syncSchema-aware mapping43 destinations available

What Contentful 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
entriescontentful_entriesUpsert by primary key, incremental on updated-at
content typescontentful_content_typesUpsert by primary key, incremental on updated-at
assetscontentful_assetsUpsert by primary key, incremental on updated-at
spacescontentful_spacesUpsert by primary key, incremental on updated-at
localescontentful_localesUpsert by primary key, incremental on updated-at
publish eventscontentful_publish_eventsAppend-only, incremental by timestamp

Popular destinations for Contentful

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

Contentful connector FAQ

What Contentful data does the connector extract?
6 objects: entries, content types, assets, spaces, locales and publish events. Each lands in its own table with types preserved; history-style objects (1: publish events) load as append-only streams.
Is the Contentful 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 Contentful data?
Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each Contentful → 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 Contentful pipeline with guided onboarding

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