Diagram and Sync Your Aurora MySQL Clusters

Aurora MySQL speaks the MySQL 8 protocol on top of Amazon's distributed storage, so DbSchema connects with the standard MySQL JDBC driver — and turns the cluster into ER diagrams, shareable documentation, and ALTER scripts you read before they run.

Reverse engineer the writer endpoint into diagrams of every table, key, and index
Diff the cluster against a development MySQL instance and review the generated ALTER statements
Keep separate connection profiles for the writer and the reader endpoints
No driver hunt — the MySQL JDBC driver downloads on first connect

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DbSchema showing an Aurora MySQL cluster as an ER diagram with documentation

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Aurora Scales the Storage
Nobody Scales the Understanding

An Aurora cluster hides its operations well: failover is automatic, replicas appear on demand, storage grows on its own. The schema inside gets no such service — it drifts away from the development MySQL boxes, and the only diagram lives in someone's head.

DbSchema reverse engineers the cluster into a model your team can open: diagrams arranged by domain, documentation for every table, and changes reviewed before they reach the writer endpoint.

Diagram, Compare & Query
the Cluster Without Guesswork

One model file covers the diagramming, the diffing, and the day-to-day queries.

Reverse engineer an Aurora MySQL cluster into an ER diagram

Your Cluster, Reverse Engineered

Point DbSchema at the writer endpoint and get ER diagrams of tables, foreign keys, and indexes — the whole schema laid out in minutes, ready to annotate and share.

Compare Aurora MySQL and development MySQL schemas

Catch Drift Against Upstream MySQL

Production Aurora and development MySQL drift apart during feature work. Diff them side by side and generate exactly the ALTER statements that close the gap.

Run SQL against Aurora MySQL writer and reader endpoints

One Editor, Two Endpoints

Write MySQL-dialect SQL with schema-aware autocomplete, and keep analytical work on a reader-endpoint profile so the writer node stays clear.

AWS Hosts the Cluster
You Keep the Design

The schema lives in a DbSchema model file on your side of the cloud. Edit it offline, version it in Git, and decide when — and as which SQL — it reaches Aurora.

Model Off the Cloud

Draft tables and relationships with no connection and no running cluster.

History in Your Repo

Commit the model file; every schema change becomes a reviewable diff.

ALTER Statements Up Front

Inspect the exact SQL a change will execute before Aurora sees it.

Apply the same change to each Aurora environment

Environments in Lockstep

Apply the same approved change to staging and production clusters in turn.

Aurora MySQL Connection Facts

Aurora MySQL is wire-compatible with MySQL 8, so DbSchema connects through the standard MySQL JDBC driver, downloaded automatically on first connect. For schema changes and DDL, target the cluster writer endpoint on port 3306: jdbc:mysql://cluster.cluster-id.region.rds.amazonaws.com:3306/dbname.

For read-heavy work, add a second profile for the reader endpoint (cluster.cluster-id-ro.region.rds.amazonaws.com). IAM authentication works as well: generate a short-lived token with the AWS SDK, supply it as the password, and enable TLS with ?useSSL=true&requireSSL=true.

Put the Aurora Cluster on One Diagram

Free Community Edition, no signup — the 15-day Architect trial is in the same installer.

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Frequently asked questions

Yes. DbSchema connects to Aurora MySQL using the standard MySQL JDBC driver, since Aurora MySQL is compatible with MySQL 8, so no extra driver installation is needed.

Aurora MySQL uses the standard MySQL port 3306 for both the cluster writer endpoint and the reader endpoint.

Yes, DbSchema's schema comparison tool connects to two environments at once, or checks a live cluster against a saved model, and generates the ALTER statements needed to align them (Pro feature).

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