Apache Iceberg

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PREVIEW This feature is in public preview. It is under active development and may have stability or performance issues. It isn't subject to our backwards compatibility guarantees.

Iceberg sinks provide exactly once delivery of updates from Materialize into Apache Iceberg¹ tables. As data changes in Materialize, the corresponding Iceberg tables are automatically kept up to date. You can sink data from a materialized view, a source, or a table.

Materialize reaches your tables through an Iceberg catalog. Follow the guide for the catalog hosting them:

AWS S3 Tables², which authenticates through an AWS connection.
GCP BigLake³ (feature in private preview) , which authenticates through a GCP connection.
Databricks Unity Catalog⁴ on AWS, which authenticates with the OAuth2 credentials of a Databricks service principal.

Apache Iceberg is an open table format for large-scale analytics datasets. ↩︎
Amazon S3 Tables is an AWS feature that provides fully managed Apache Iceberg tables as a native S3 storage type. ↩︎
Google Cloud BigLake provides a managed Apache Iceberg REST catalog over Google Cloud Storage. ↩︎
Databricks Unity Catalog exposes its tables to Apache Iceberg clients through an Iceberg REST catalog endpoint. ↩︎