Map Redshift Distribution and Sort Keys Visually

Redshift query performance is set by distribution styles and sort keys — design decisions ordinary SQL tools keep invisible. DbSchema reverse-engineers the cluster into an ER diagram, lets you compare environments, and generates the sync script you read before it touches production.

Distribution styles (KEY, ALL, EVEN) and sort keys made visible
Validate the layout against expected join patterns before committing
Diff dev and production clusters; get the ALTER and CREATE statements
Publish warehouse docs for consumers without cluster access

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DbSchema displaying an Amazon Redshift warehouse schema as an ER diagram

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Warehouse Performance Is Decided
Before the First Query Runs

A wrong distribution key means data shuffled between nodes on every join; a missing sort key means scans that should have been skips. These choices live in the DDL, and the query editor never shows them side by side with the relationships they serve.

DbSchema puts the whole warehouse on one canvas — tables, foreign-key relationships, and the layout decisions data engineers need to check against real join patterns.

Design, Compare & Document
the Redshift Warehouse

From ad-hoc questions to governed schema promotion.

Build Redshift queries visually in DbSchema

Joins and Aggregations by Click

Assemble joins, WHERE conditions, and aggregations visually; the generated SQL runs on the cluster and the results come back inline — the Redshift console stays closed.

Synchronize schemas between Amazon Redshift clusters

Promote Changes Between Clusters

Compare the DDL state of two environments and get the ALTER and CREATE statements that close the gap — manual diffing out, reviewable scripts in.

Export Amazon Redshift schema documentation as HTML

Docs Instead of Warehouse Logins

Export browsable HTML with ER diagrams and table definitions, so report developers and auditors get an up-to-date reference without direct cluster access.

Treat Warehouse DDL
Like Application Code

The Redshift schema lives in a design model file you keep in your repository — branch it, diff it, review it in a pull request. Approved changes become the ALTER and CREATE statements that move from the development cluster to production, one sign-off at a time.

Amazon Redshift schema synchronization between the Git model and clusters

Read Git Workflow Docs

Cluster, Serverless, IAM: Connection Notes

Pick Amazon Redshift in the connection dialog and DbSchema downloads the JDBC driver automatically. Supply the cluster endpoint, port 5439, database name, and credentials — together they form jdbc:redshift://cluster.region.redshift.amazonaws.com:5439/dbname. The cluster's VPC security group must allow inbound TCP on 5439 from the machine running DbSchema.

Redshift Serverless connects the same way with the workgroup endpoint in place of the cluster endpoint — URL shape and port are unchanged. IAM authentication works through the IAMAuth JDBC property. See the Redshift JDBC driver page for the full setup.

Bring Your Redshift Schema Into View

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Frequently asked questions

Yes — DbSchema connects to your Redshift cluster, reverse-engineers the full schema, and renders it as a navigable ER diagram showing table structures and FK relationships.

Redshift listens on port 5439 by default, so the cluster's VPC security group must allow inbound TCP traffic on that port from the machine running DbSchema.

Yes — for Redshift Serverless deployments, use the workgroup endpoint in place of a cluster endpoint; the JDBC URL structure and port stay the same, and IAM authentication is supported through the IAMAuth JDBC property.

Teams working with Amazon Redshift often use these engines too. Explore dedicated guides and JDBC setup for each.