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 Microsoft Fabric Lakehouse, 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 Microsoft Fabric Lakehouse are listed in the section below.
Microsoft Fabric Lakehouse is a unified data lakehouse platform within Microsoft Fabric that combines the flexibility of data lake storage with the structure and query performance of a data warehouse. It stores data in Delta Lake format on OneLake and exposes a SQL Analytics Endpoint for standard SQL querying using familiar tools. Fabric Lakehouse integrates with Power BI, Azure Synapse, and other Microsoft data services for end-to-end analytics.
Microsoft Fabric Lakehouse provides a SQL Analytics Endpoint accessible via the SQL Server JDBC driver on port 1433. Authentication requires Azure Active Directory credentials. The connection string is available from the Fabric workspace settings. Use encrypt=True;trustServerCertificate=False for production connections.
DbSchema connects to Microsoft Fabric Lakehouse via the SQL Analytics Endpoint using the SQL Server JDBC driver, enabling visualization of Delta Lake table schemas, SQL query execution against Fabric Lakehouse data, and schema documentation for enterprise data lakehouse architectures.
Have connection issues? Contact the DbSchema team for help.
Once the JDBC driver is configured, DbSchema connects to your Microsoft Fabric Lakehouse 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 Microsoft Fabric Lakehouse 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 Microsoft Fabric Lakehouse 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 Microsoft Fabric Lakehouse 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 Microsoft Fabric Lakehouse 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 Microsoft Fabric Lakehouse 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 Microsoft Fabric Lakehouse 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.