Metadata Management: Both metastores and catalogs manage metadata, but catalogs typically offer more advanced metadata management features.
Data Discovery and Governance: Catalogs provide more robust tools for data discovery, lineage tracking, and governance, whereas metastores focus primarily on storing and retrieving metadata.
Integration: Metastores can be a component within a catalog, providing the necessary metadata storage while the catalog offers additional functionalities for data governance and discovery.
Metastores:
Purpose: Metastores store metadata about the data assets in a system. Metadata includes information such as the schema, data types, location of the data, and other descriptive details.
Scope: Typically, a metastore provides a centralized repository for metadata across various data sources and databases.
Usage: Used by data processing engines to understand the structure and location of data, enabling efficient query execution and data management.
Examples: Hive Metastore, AWS Glue Data Catalog.
Catalogs:
Purpose: Catalogs provide a higher-level organizational structure for datasets, offering additional metadata management, data discovery, and governance capabilities.
Scope: Catalogs often include features for tagging, lineage tracking, data quality, and access control, making it easier to manage data assets within an organization.
Usage: Used by data stewards, analysts, and data scientists to discover, understand, and govern data assets. Catalogs may integrate with metastores to provide a comprehensive view of data.
Examples: Databricks Unity Catalog, Azure Purview, Alation Data Catalog.
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