Download GoogleBigQuery JDBC Driver

Download the GoogleBigQuery JDBC driver, copy the JDBC URL into DbSchema, and start designing schemas with ER diagrams — free Community Edition.

About the GoogleBigQuery JDBC driver

A JDBC driver is a Java .jar library that lets applications connect to GoogleBigQuery. DbSchema uses JDBC to reverse engineer schemas, run SQL, and generate documentation. Driver files are usually published by the database vendor or an open-source project.

JDBC URL format

Host, port, database name, and SSL options are passed in a URL starting with jdbc:. Each GoogleBigQuery driver uses its own syntax — see the connection details below.

The GoogleBigQuery JDBC driver

Google BigQuery is a fully managed, serverless data warehouse that enables super-fast SQL queries against multi-petabyte datasets. It uses a columnar storage format (Capacitor) and a massively parallel query engine, making it ideal for BI, ML feature engineering, and large-scale reporting.

The Google BigQuery JDBC URL

• Required File(s): googlebigqueryjdbc42.jar
• Java Driver Class: com.simba.googlebigquery.jdbc42.Driver
• JDBC URL: jdbc:bigquery://https://www.googleapis.com/bigquery/v2:443;ProjectId=DB;OAuthType=1;
• Website: Google BigQuery

Download Google BigQuery JDBC Driver

The driver archive is a zip file. Extract it and load the .jar files using DbSchema's Driver Manager.

Set Up the BigQuery Connection

BigQuery has no host or port to fill in — the endpoint is fixed and already in the URL. What you supply is a project and a way to prove who you are.

1. Give the project id. ProjectId is the project that runs and is billed for the queries. It is the project id, not the display name, and not necessarily the project the data lives in — you can query datasets in another project from here.
2. Pick how you authenticate. The Connection Mode combo maps to the driver's OAuthType values. Google Service Account is the usual choice for a desktop tool: it takes the service account's email and the path to its key file. Google User Account runs a browser sign-in, Access Tokens takes tokens you already hold, and Application Default Credentials uses whatever gcloud auth application-default login left on the machine.
3. Grant the account the right roles. Reading a schema needs BigQuery data viewer rights on the datasets and job user rights on the project. Missing job rights is a common trap: the dataset list appears, then every query fails.
4. Allow outbound HTTPS. Everything goes to www.googleapis.com on port 443. There is no inbound firewall rule to write; a proxy that intercepts TLS is the only usual obstacle.
5. Paste the URL into DbSchema. In the Connection Dialog set Connection Mode to Edit the JDBC URL Manually and paste the string you copied. The user and the password are entered in the first tab, not in the URL.

To reach a custom endpoint, choose Edit the JDBC URL Manually — the host is otherwise fixed by the preset.

DbSchema and Google BigQuery

DbSchema maps BigQuery datasets and tables into visual ER diagrams, helping analysts understand the relationships between fact and dimension tables in a data warehouse schema. Use the SQL Editor to write BigQuery Standard SQL with partitioning filters, nested STRUCT queries, and ARRAY aggregations.