DOCS
← Back to Glossary
schema
A schema is a logical container or blueprint that defines how data is organized within a database.
Definition
A schema is a logical container or blueprint that defines how data is organized within a database. It specifies the structure of tables, the data types of columns, and the relationships between different tables, often established through foreign keys. Think of a schema like the architectural plans for a house - it shows where everything goes and how the pieces fit together, but doesn't contain the actual data (furniture) itself.
Usage in DuckDB
In DuckDB, schemas provide a way to organize database objects like tables and views into namespaces. The default schema is called main. Unlike some other databases that require explicit schema creation, DuckDB automatically creates the main schema and allows you to reference objects within it directly.
You can create additional schemas using:
Copy code
CREATE SCHEMA marketing;
And reference objects within a schema using dot notation:
Copy code
CREATE TABLE marketing.campaigns (
id INTEGER,
name VARCHAR
);
Key Differences
While enterprise databases like PostgreSQL use schemas extensively for access control and multi-tenant applications, DuckDB's implementation is primarily focused on logical organization. DuckDB doesn't implement schema-level security since it's an embedded database without user management. Additionally, DuckDB allows you to query across schemas without explicit cross-schema permissions that might be required in other databases.
Best Practices
For smaller projects, using the default main schema is perfectly acceptable. However, as your data model grows, using multiple schemas can help organize related tables and views together. For example, you might have separate schemas for raw data ingestion, transformed data models, and reporting views. This organization makes it easier to understand and maintain your database structure over time.
Related terms
Schema registry →
A schema registry is a centralized service that stores, versions, and validates data schemas — typically for Avro, Protobuf, or JSON Schema — used to keep producers and consumers in streaming systems like Kafka compatible as schemas change.
Schema evolution →Schema evolution is the ability to change a table's structure — adding, removing, renaming, or reordering columns, or widening types — over time without needing to rewrite all existing data or break existing readers.
table →A table is a fundamental structure in a relational database that organizes data into rows and columns, similar to a spreadsheet.
data model →A data model is a conceptual representation of how data is structured, organized, and related within a system or database.
Star schema →A star schema is a dimensional data warehouse design where a central fact table of numeric measures connects directly to denormalized dimension tables, forming a shape like a star.
relational database →A relational database is a structured collection of data organized into tables with rows and columns.
FAQS
A schema is a logical container that defines how data is organized—table structures, column data types, and relationships between tables. It's the blueprint, not the data itself.
main. DuckDB creates it automatically and lets you reference objects in it directly, without explicit schema creation.
Run CREATE SCHEMA name; and then reference objects with dot notation, e.g. CREATE TABLE marketing.campaigns (...).