---
title: "Data catalog"
description: "A data catalog is a centralized inventory of an organization's datasets, tracking metadata like schema, location, lineage, and ownership so people and systems can discover, understand, and access data."
canonical: "https://motherduck.com/glossary/data-catalog/"
related:
  - title: "From Data Lake to Lakehouse: Can DuckDB be the best portable catalog?"
    url: "https://motherduck.com/blog/from-data-lake-to-lakehouse-duckdb-portable-catalog/"
  - title: "DuckLake Architecture Deep Dive: Catalog, Storage, Compute | MotherDuck"
    url: "https://motherduck.com/videos/ducklake-architecture-deep-dive/"
  - title: "Apache Iceberg | MotherDuck Docs"
    url: "https://motherduck.com/docs/integrations/file-formats/apache-iceberg/"
gated_asset:
  title: "DuckLake: The Lakehouse Table Format"
  url: "https://motherduck.com/lp/ducklake-lakehouse-table-format-book-full/"
---

# Data catalog

> A data catalog is a centralized inventory of an organization's datasets, tracking metadata like schema, location, lineage, and ownership so people and systems can discover, understand, and access data.

## Overview
A data catalog is metadata about data: it doesn't store the underlying rows, but tracks what datasets exist, where they live, what their schema looks like, who owns them, and often how they relate to one another (lineage). Catalogs serve two audiences — humans, who use them to discover and understand available data, and systems, which use them to resolve table names to physical locations when planning queries.

## Catalogs in the lakehouse stack
In a lakehouse architecture, a catalog has a very concrete technical role: it maps a table name to the current metadata pointer for that table, so an engine can find the right Iceberg manifest, Delta transaction log, or DuckLake database entry to read. Common catalog implementations include the Iceberg REST catalog specification, AWS Glue Data Catalog, Hive Metastore (which predates and heavily influenced the others), and Databricks' Unity Catalog.

## Beyond table resolution
Enterprise data catalogs (like Alation or Collibra) go further, layering in business glossaries, data quality metrics, access controls, and search across data warehouses, lakes, BI tools, and dashboards — helping analysts find "the right" table among many similarly named ones.

## Catalogs and DuckDB
DuckDB can attach to lakehouse catalogs to resolve and query tables managed by other engines. For Iceberg, this means attaching a REST catalog directly:

```sql
INSTALL iceberg;
LOAD iceberg;

ATTACH 'my_warehouse' AS my_iceberg (
    TYPE iceberg,
    ENDPOINT 'https://catalog.example.com'
);

SELECT * FROM my_iceberg.sales.orders;
```

MotherDuck also functions as a catalog and query layer of its own — databases and schemas shared through MotherDuck act as a discoverable catalog of tables that any attached DuckDB client can query.