A JDBC driver is a Java library file (.jar) that enables Java applications — including DbSchema — to communicate with a database over a standard API. The driver translates generic JDBC calls into the network protocol understood by Yellowbrick, so you never have to write low-level socket code. Drivers are typically distributed by the database vendor or as open-source projects.
Every JDBC driver identifies the target database through a connection URL. The URL encodes the hostname, port, database name, and any driver-specific parameters as a single string. The exact syntax varies per driver — the details for Yellowbrick are listed in the section below.
Yellowbrick is a hybrid cloud data warehouse built for demanding analytical workloads, combining an in-memory columnar engine with NVMe flash storage for extreme query performance. It uses a massively parallel processing (MPP) architecture and is compatible with PostgreSQL tooling, making migrations straightforward. Yellowbrick is optimized for large-scale analytics across on-premises and cloud deployments.
Yellowbrick uses a PostgreSQL-compatible wire protocol on port 5432. The Yellowbrick JDBC driver provides optimized connectivity for the Yellowbrick MPP engine. SSL can be enabled via connection properties.
DbSchema connects to Yellowbrick using the Yellowbrick JDBC driver, visualizing MPP analytical schemas including distribution keys and columnar storage configurations, and enabling complex analytical SQL authoring for large-scale data warehousing workloads.
Have connection issues? Contact the DbSchema team for help.
Once the JDBC driver is configured, DbSchema connects to your Yellowbrick database and gives you a full graphical workbench — no command-line required. Available as a free Community Edition and a full-featured PRO Edition. No registration needed to get started.
Reverse-engineer your Yellowbrick schema into a drag-and-drop ER diagram. Arrange tables visually, add new columns, define foreign keys, and let DbSchema generate the DDL — all without writing SQL by hand.
Compose Yellowbrick queries by clicking on tables and columns — no SQL knowledge required. Add joins, filters, groupings, and aggregations through a point-and-click interface, then copy the generated SQL or run it directly against the live database.
Browse Yellowbrick table data and follow foreign key relationships across tables in a single view. Edit cells inline, filter rows, and paginate through large datasets — all without leaving the explorer.
Compare your Yellowbrick schema across development, staging, and production environments. DbSchema generates the exact ALTER statements needed to close the gap and lets you review every change before executing — reducing the risk of unintended schema drift.
Write and execute Yellowbrick queries in the integrated SQL editor with schema-aware autocomplete, syntax highlighting, and instant result display. Run scripts, inspect execution plans, and export results to CSV or JSON from a single interface.
Generate a static HTML site documenting every table, column, type, index, and relationship in your Yellowbrick schema. Share it with your team or embed it in your project wiki — no extra tooling required.
For the full feature list and edition comparison, visit the DbSchema PRO Edition page.