Databases

How To Install MySQL Workbench 8 on macOS

Josphat Mutai Updated Mar 16, 2026 · 1 min read

In this article we look at the installation of MySQL Workbench 8 on a macOS system. MySQL Workbench is a Desktop application that enables Developers and Database Administrators to perform SQL server administration, development, design, as well as maintenance from a single integrated development environment.

Original content from computingforgeeks.com - post 75360

As of this article update the latest release of MySQL Workbench is version 8. There are many new features in this release which can be checked on MySQL Workbench 8.0 Release notes. To download the latest MySQL Workbench 8 for macOS visit the official downloads page.

How To Install MySQL Workbench 8 on macOS 01

Here is a quick download command using wget for the latest available release as of this article writing.

wget https://dev.mysql.com/get/Downloads/MySQLGUITools/mysql-workbench-community-8.0.41-macos-x86_64.dmg

Wait for the download to complete then double-click on the file to start the installation. Or start from CLI:

open mysql-workbench-community-8.0.41-macos-x86_64.dmg

Proceed with the installation of MySQL Workbench on macOS. Drag the file to move it to the Applications folder

How To Install MySQL Workbench 8 on macOS 02

You should see the file being copied to the Applications directory.

How To Install MySQL Workbench 8 on macOS 03

Search for the “MySQL Workbench Application” and start it.

How To Install MySQL Workbench 8 on macOS 04

More guides on macOS:

Josphat Mutai

Founder of Computingforgeeks. Senior Systems Engineer with over a decade of hands-on experience building and managing production infrastructure. Core expertise in Linux/UNIX administration, cloud platforms (AWS, GCP, Azure), and Kubernetes ecosystems (EKS, GKE, OpenShift). Deep experience with virtualization (KVM, Proxmox, OpenStack), infrastructure as code (Terraform, Terragrunt, Ansible, Crossplane), GitOps workflows (ArgoCD, FluxCD), Nix/NixOS, and container orchestration at scale. Currently focused on integrating AI and LLMs into DevOps and platform engineering workflows. Every guide on this site is tested on real systems before publishing.

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