How to Design Schemas in Amazon Redshift

How do I design a schema in Amazon Redshift?

CREATE SCHEMA groups tables, views, and other objects under a namespace, simplifying organization, security, and query performance tuning.

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Description

Why create separate schemas in Redshift?

Separate schemas isolate business domains, simplify permission management, and keep query search paths short for faster planning. In an ecommerce cluster, store customer-facing tables in a public schema and analytics tables in a reporting schema.

What is the CREATE SCHEMA command?

CREATE SCHEMA builds a named namespace, optionally assigning an owner and granting default privileges. You can also create multiple objects inside a single statement, but most teams prefer one object per migration file for version control clarity.

How do I design a schema step-by-step?

1. Choose a clear name

Use lowercase, snake_case names like sales, analytics, or stage. Avoid generic names such as data or misc.

2. Set ownership and privileges

Grant ownership to a role like analytics_role, then grant USAGE on the schema to read-only roles. This enforces least privilege.

3.Define distribution and sort keys

When you create tables inside the schema, pick DISTKEY and SORTKEY columns that match common joins and time filters to minimize data shuffling.

How do I create tables inside the schema?

Reference the schema explicitly (sales.customers) or set SET search_path TO sales; before CREATE TABLE statements. Explicit references reduce ambiguity in multi-schema environments.

What are best practices?

Keep staging, operational, and reporting data in separate schemas.
Prefix foreign key columns with the parent table name for clarity (customer_id).
Store rarely joined lookup tables with DISTSTYLE ALL to speed up joins.
Document schema purpose and owner in a README table or wiki.

Code example: full migration

The example below creates a schema, grants access, and builds a table with proper keys.

BEGIN; -- Schema CREATE SCHEMA sales AUTHORIZATION analytics_role; GRANT USAGE ON SCHEMA sales TO readonly_role; -- Table CREATE TABLE sales.customers ( id BIGINT IDENTITY(1,1), name VARCHAR(100), email VARCHAR(255), created_at TIMESTAMP ) DISTKEY(id) SORTKEY(created_at); COMMIT;

Encouraging next step

Iterate on your schema design during development sprints and monitor query plans to confirm that DIST/SORT choices remain optimal.

Why How to Design Schemas in Amazon Redshift is important

How to Design Schemas in Amazon Redshift Example Usage


-- List all tables in the sales schema
SELECT table_name
FROM information_schema.tables
WHERE table_schema = 'sales'
  AND table_type = 'BASE TABLE'
ORDER BY table_name;

How to Design Schemas in Amazon Redshift Syntax


CREATE SCHEMA [IF NOT EXISTS] schema_name
    [AUTHORIZATION user_or_role]
    [QUOTA size]
    [CREATE TABLE statement …];

-- Example for ecommerce context
CREATE SCHEMA sales AUTHORIZATION analytics_role;

-- Creating tables within the new schema
CREATE TABLE sales.orders (
    id           BIGINT IDENTITY(1,1),
    customer_id  BIGINT,
    order_date   DATE,
    total_amount DECIMAL(10,2)
) DISTKEY(customer_id) SORTKEY(order_date);

Common Mistakes

Using the default public schema for everything. This crowds the namespace, complicates permissions, and slows query planning. Fix: create purpose-specific schemas and set search_path explicitly.
Ignoring DISTKEY/SORTKEY during initial table creation. Redshift requires a deep copy to change them later. Fix: profile queries first and set keys when you create tables within the schema.