clickhouse integration stitch data — Close the Destination Gap in 2026

Stitch, a managed ELT extraction tool, efficiently extracts data from various sources like Salesforce and HubSpot but does not natively support ClickHouse as a destination, requiring a workaround strategy for integration. To effectively use Stitch with ClickHouse, data must first be landed in object storage such as S3 or GCS before being loaded into ClickHouse, where users are responsible for setting up table engines and sort keys. This process involves using object storage as an intermediary, allowing ClickHouse to efficiently read data formats like Parquet, JSON, or CSV while enabling users to control the MergeTree design for data upserts. Stitch is praised for its source connectors, incremental replication, and ability to deliver data into supported destinations like Snowflake, BigQuery, and Redshift, but the gap in ClickHouse support necessitates a deliberate landing strategy. Users must account for schema drift, watermark logic, and freshness expectations, especially when integrating Stitch for product analytics, where a secondary hop into ClickHouse or a platform like Tinybird might be necessary for interactive analytics.

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