# Catalogs

Most analytical data is stored in cloud object stores like Amazon S3, GCS, or Azure Blob Storage. However, structural metadata such as table names, schemas, and partitions managed by metastores like Hive, AWS Glue, Dataproc Metastore, Unity Catalog, or Apache Polaris.

In e6data, a Catalog connects to these metastores to provide the metadata needed for querying data stored in object stores efficiently.

| Catalog Service                                                                                             | Description                                                      |
| ----------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------- |
| [**Hive Metastore**](https://docs.e6data.com/product-documentation/catalogs/create-catalogs/hive-metastore) | Traditional metastore widely used with Hadoop and Spark.         |
| [**Glue Metastore**](https://docs.e6data.com/product-documentation/catalogs/create-catalogs/glue-metastore) | AWS-managed metastore with schema versioning and S3 integration. |
| [**Unity Catalog**](https://docs.e6data.com/product-documentation/catalogs/create-catalogs/unity-catalog)   | Databricks’ unified metadata and governance layer.               |
| [**Apache Polaris**](https://docs.e6data.com/product-documentation/catalogs/create-catalogs/apache-polaris) | REST-based Iceberg catalog for scalable metadata management.     |

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Cross-account support requires specific IAM configuration depending on the cloud provider.
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