A JDBC driver is a Java library file (.jar) that enables Java applications to communicate with a database. The JDBC is a standard interface implemented by each database with a specific driver. Drivers are typically distributed by the database vendor or as open-source projects.
The connection parameters including the database location, database name and connection method are passed to the driver using the JDBC URL. The JDBC URL is a text starting with 'jdbc:...' which combines the hostname, port, database name, and any driver-specific parameters. The exact syntax can be different for each JDBC driver.
Apache Druid is a high-performance, real-time analytics database designed for large-scale event-driven data and sub-second OLAP queries. It ingests streaming and batch data, stores it in columnar segments, and serves fast aggregations at scale. Druid is widely used for operational analytics, dashboards, and applications requiring real-time query performance.
Connect to the Druid Broker node on port 8082. The Avatica driver is included with the Druid distribution or available separately from Apache Calcite. No additional authentication configuration is required for basic setups, though TLS and Kerberos can be enabled for secured clusters.
DbSchema uses the Avatica JDBC driver to connect to Apache Druid's SQL interface, rendering datasource schemas and enabling interactive SQL editing against Druid's real-time OLAP engine. Use the data explorer to browse ingested segments and their column distributions.
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Reverse engineer an existing database or open a sample model to explore tables, relations, and indexes visually.
Edit your schema, generate interactive documentation, and roll out reviewed changes across environments.
Once the JDBC driver is configured, DbSchema connects to your Apache Druid 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 Apache Druid 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 Apache Druid 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 Apache Druid 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 Apache Druid 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 Apache Druid 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 Apache Druid 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.
ER diagrams, Git-based versioning, random data generator, and HTML schema docs.