DbSchema lets you design, manage, and document Aurora MySQL databases. Create ER diagrams, define tables and columns, and generate SQL scripts - with or without a live database connection.
Use Git to share the design, compare it with the Aurora MySQL database, and deploy changes. DbSchema also includes a data editor, query builder, and HTML5 documentation - everything you need in one tool.
Download DbSchema Download Aurora MySQL JDBC Driver
Amazon Aurora MySQL is a cloud-native relational engine designed to deliver up to five times the throughput of standard MySQL by decoupling compute from distributed storage. Clusters expose a writer endpoint and one or more reader endpoints, and schemas evolve independently of instance scaling. DbSchema connects to Aurora MySQL using the standard MySQL JDBC driver — the same driver used for any MySQL 8-compatible database — so there is no extra driver installation required.
DbSchema introspects the Aurora cluster schema and renders every table, column, foreign key, and index as a navigable ER diagram. You can group related tables into diagram layouts, annotate relationships, and share diagrams with your team as HTML documentation — without keeping a live connection open.
Production Aurora clusters frequently diverge from development MySQL instances during feature work. DbSchema's schema comparison tool connects to two environments simultaneously — or compares a live cluster against a saved schema file — and generates the exact ALTER statements needed to bring them back into alignment. You review the diff before any SQL runs.
The built-in SQL editor supports the full MySQL dialect and Aurora-specific extensions such as parallel query
hints and SELECT INTO OUTFILE S3. You can maintain separate connection profiles for the writer
endpoint and the reader endpoint, keeping analytical queries off the writer node.
Aurora MySQL uses the standard MySQL JDBC driver, which DbSchema downloads automatically. Use the cluster
writer endpoint for schema changes and DDL operations:
jdbc:mysql://cluster.cluster-id.region.rds.amazonaws.com:3306/dbname.
For read-heavy workloads, point a separate profile at the reader endpoint
(cluster.cluster-id-ro.region.rds.amazonaws.com).
IAM database authentication is also supported: generate a short-lived token via the AWS SDK and supply it as
the password with SSL enabled (?useSSL=true&requireSSL=true). The default port is 3306.