Data Lakehouse capabilities for Snowflake projects

Qlik Talend Cloud pipelines introduces two new features to build open lakehouses with Snowflake. These features can be used independently or in combination.

Lake-landing ingestion for Snowflake pipelines

The lake-landing task allows to replicate data to your cloud storage of choice in low latency. The downstream Snowflake storage layer can be scheduled to consume the ingested data at a slower pace. This capability reduces warehouse compute uptime requirements.

Support for Snowflake-managed Iceberg tables

Storage, Transform and Data mart tasks can be configured to store data on an external cloud storage (Amazon S3, Azure Data Lake Storage, or Google Cloud Storage) as Snowflake-managed Iceberg tables. Iceberg tables are managed by Snowflake and can be synchronized with Snowflake Open Catalog (previously called Snowflake Polaris) for full interoperability with any Iceberg-compatible engine.

Landing data to a lakehouse