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A data catalog is a central registry that tracks a table’s schema, partitions, and file locations, so a query engine can look those up instead of scanning a bucket to rediscover them. If your tables are already registered in one of the catalogs below, StarTree reads that registry directly — you get schema inference, partition awareness, and incremental snapshot sync for free, instead of the raw file-scanning approach in Query Parquet Directly.

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Which catalog do you have?

All four are reached the same way — catalogType=iceberg-rest — over the Iceberg REST protocol; only the service endpoint and authentication differ.
CatalogWhat it isOnboarding guide
AWS GlueAWS’s managed Iceberg REST catalog, backed by the Glue Data CatalogOnboarding via API · via Data Portal
Amazon S3 TablesAWS’s managed Iceberg tables, addressed by table-bucket ARNOnboarding via API · via Data Portal
Unity CatalogDatabricks-managed or OSS Unity Catalog — also covers Delta Lake tables with UniForm enabledOnboarding via API
NessieA Git-like, branch/ref-aware Iceberg catalog, self-hosted or managedOnboarding via API
Not sure which authentication method to use for your catalog, or whether a given feature (assumed-role auth, vended credentials, OAuth2) is supported? Each catalog’s onboarding guide has an Authentication section with a runnable config sample per method.

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How onboarding works, regardless of catalog

Every catalog above follows the same four calls: validate & browse the connection, preview to infer a schema, create the schema, then create the table — after which the controller’s watcher takes over and syncs on a schedule with no further manual steps. Each catalog’s onboarding guide walks through all four with runnable examples.

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What’s next

Once the table is created, add indexes for the columns you filter and group by, enable caching, and track sync health through Observability.