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About dbvr

dbvr is a database management CLI from DBeaver. It’s designed for automation-first, headless workflows, where database operations run without a graphical interface.

dbvr fits well into CI/CD pipelines, server-side scripts, containers, and remote environments. It’s built for repeatable runs, predictable results, and logs you can use to troubleshoot automated executions.

Note

dbvr is a CLI-only product and doesn’t provide a graphical user interface.

dbvr is designed with the following characteristics:

  • Broad database support: dbvr works with a wide range of relational, NoSQL, and cloud databases through a single CLI, so you don’t need separate tools per database type.
  • Automation-first design: built for scripting and integration into CI/CD pipelines, scheduled jobs, and infrastructure workflows.
  • Headless execution: designed to run on servers, containers, and remote environments without a desktop or browser.
  • Consistent behavior: operations behave the same across environments, which helps keep automation reliable and reproducible.
  • Lightweight runtime: no GUI overhead, reduced resource usage, and fast startup.

dbvr capabilities

dbvr supports database operations that are commonly executed programmatically as part of automated workflows.

  • Connection management: work with database connections in CLI workflows.
  • SQL execution: execute SQL queries and scripts from the command line.
  • Data transfer: export query results in common formats either locally or in the cloud.

Tip

For information on using dbvr together with DBeaver, see Setting up dbvr with DBeaver.

Who dbvr is for

dbvr is intended for teams that run database work from scripts and pipelines, not from a desktop UI.

Common audiences include:

  • DevOps engineers and SREs running migrations, checks, and validation in CI/CD
  • software developers scripting local setup, tests, and repeatable data prep
  • DBAs managing remote, headless servers over SSH
  • data engineers exporting data for ETL/ELT workflows
  • platform and cloud engineers packaging database tooling into containers and Kubernetes jobs

Where dbvr fits

dbvr fits naturally into automated workflows where database operations are executed programmatically.

  • CI/CD pipelines for validating database state before or after deployment
  • backup and restore processes for verifying schemas and tables
  • test environments for preparing, validating, and cleaning up data
  • analytics workflows for scheduled data exports
  • server and container environments where no GUI is available