> ## Documentation Index
> Fetch the complete documentation index at: https://docs.e6data.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Hive tables

> How e6data queries Hive tables through a Hive Metastore or compatible catalog.

e6data queries **Hive tables** - data registered in a Hive Metastore (or a compatible catalog) and stored in object storage. Hive remains a common format for Hadoop- and Spark-based data lakes.

## How it works

e6data connects to your metastore through a catalog, reads the table and partition metadata, and reads the underlying data files directly from object storage (S3, ADLS Gen2). e6data is read-only - it discovers and queries Hive tables but does not modify the metastore or the data.

## What's supported

* Reading Hive tables via the [Hive Metastore](/query/catalogs/hive-metastore) catalog, and via [AWS Glue](/query/catalogs/aws-glue) where Hive-style tables are registered in Glue.
* Partitioned and non-partitioned tables, with partition pruning at query time.
* Common open file formats stored under Hive tables (such as Parquet and ORC).

## Connect to Hive tables

There is no separate "Hive tables" catalog type - connect the catalog that manages your Hive tables:

1. Open the **Catalogs** section and select **Create Catalog**.
2. Choose [Hive Metastore](/query/catalogs/hive-metastore) (or [AWS Glue](/query/catalogs/aws-glue) if your Hive tables are registered in Glue).
3. Provide the connection details and the schemas to expose.

See the catalog guides for the full connection steps, including cross-account access.

## See also

* [Hive Metastore](/query/catalogs/hive-metastore)
* [AWS Glue Catalog](/query/catalogs/aws-glue)
* [Iceberg](/query/table-formats/iceberg) · [Delta Lake](/query/table-formats/delta-lake)


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.