> ## Documentation Index
> Fetch the complete documentation index at: https://docs.startree.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Getting Started: Connect a Data Catalog

> Connect StarTree to an Iceberg-compatible data catalog — AWS Glue, Amazon S3 Tables, Unity Catalog, or Nessie — and onboard a registered table as an External Table.

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](./query-without-a-catalog).

## 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.

| Catalog              | What it is                                                                                                                                      | Onboarding guide                                                                                         |
| -------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------- |
| **AWS Glue**         | AWS's managed Iceberg REST catalog, backed by the Glue Data Catalog                                                                             | [Onboarding via API](../glue/onboarding-api) · [via Data Portal](../glue/onboarding-data-portal)         |
| **Amazon S3 Tables** | AWS's managed Iceberg tables, addressed by table-bucket ARN                                                                                     | [Onboarding via API](../s3tables/onboarding-api) · [via Data Portal](../s3tables/onboarding-data-portal) |
| **Unity Catalog**    | Databricks-managed or OSS Unity Catalog — also covers Delta Lake tables with [UniForm](https://docs.delta.io/latest/delta-uniform.html) enabled | [Onboarding via API](../unity/onboarding-api)                                                            |
| **Nessie**           | A Git-like, branch/ref-aware Iceberg catalog, self-hosted or managed                                                                            | [Onboarding via API](../nessie/onboarding-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.

## 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.

## What's next

Once the table is created, add [indexes](../indexes) for the columns you filter and group by, enable [caching](../data-and-index-caching), and track sync health through [Observability](../observability).