DatriseAI-first ETL

Source connector

Parquet File connector

Parquet File integration for databases, warehouses and BI tools

Columnar Parquet files from lakes and exports. Datrise captures Parquet File entities such as row groups, columns, schemas, partitions, file batches and column statistics, 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 `parquet_file_row_groups`) with a schema derived from the Parquet File 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 Parquet File pipeline page, and join the waitlist to get the Parquet File connector with guided onboarding.

Incremental syncSchema-aware mapping43 destinations available

What Parquet File 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
row groupsparquet_file_row_groupsUpsert by primary key, incremental on updated-at
columnsparquet_file_columnsUpsert by primary key, incremental on updated-at
schemasparquet_file_schemasUpsert by primary key, incremental on updated-at
partitionsparquet_file_partitionsUpsert by primary key, incremental on updated-at
file batchesparquet_file_file_batchesUpsert by primary key, incremental on updated-at
column statisticsparquet_file_column_statisticsUpsert by primary key, incremental on updated-at

Popular destinations for Parquet File

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
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    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
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    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

Parquet File connector FAQ

What Parquet File data does the connector extract?
6 objects: row groups, columns, schemas, partitions, file batches and column statistics. Each lands in its own table with types preserved; history-style objects (0) load as append-only streams.
Is the Parquet File 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 Parquet File data?
Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each Parquet File → 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 Parquet File pipeline with guided onboarding

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