Choose the simplest Git workflow that fits how often your team deploys, how many versions it must support, how reliable its automated tests are, and who needs permission to contribute. Trunk-based development and GitHub Flow suit frequent integration and deployment; GitFlow and release branches can help manage scheduled releases or separately maintained versions. No strategy is best for every team.
What are the six main types of Git branching strategy?
GitLab’s overview groups Git workflows into six broad families: centralized, feature branching, trunk-based development, personal branching, forking, and GitFlow. The names describe different ways to share work and manage branches; they are not all mutually exclusive. GitHub Flow and GitLab Flow, for example, are more specific workflows that build on branch-based development.
1. Centralized workflow
Everyone commits to one shared main branch. This is simple to understand and may suit a small project or one that changes infrequently. The trade-off is that concurrent work has less isolation: multiple changes meet on the same branch rather than being developed separately before integration.
main: change A → change B → change C
2. Feature branching
Each feature or fix gets its own branch, which is merged back after review. Separate branches let people work in parallel, but long-lived branches can diverge from main and make merging more involved. A team also has to manage the volume and lifecycle of its branches.
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main → feature branch → review → main
3. Trunk-based development
Developers integrate frequently into a single trunk, usually called main or trunk. AWS Prescriptive Guidance describes the practice as developers working on one such branch. Its delivery goal is to keep code continuously releasable through frequent integration, automated testing, and continuous integration.
short-lived work → frequent integration → main
This approach depends on CI and automated tests that give the team confidence in the shared branch. If integration is infrequent or the checks are not dependable, the team loses an important safeguard of the model.
4. Personal branching
Each developer works in an individual branch before sharing changes. That can isolate a person’s work, but as the team grows it can create more coordination and integration work. The relevant question is not only whether a personal branch is convenient, but how and when its changes are brought together.
Rank #2
developer A branch ─┐
developer B branch ─┴→ shared work
5. Forking workflow
Contributors work in separate repository forks and submit changes to the canonical repository. This is useful when contributors should not have direct write access to that repository, as is common in many open-source projects. The separation is primarily about repository access and contribution, not about a required release cadence.
canonical repository ← proposed change ← contributor fork
6. GitFlow
GitFlow uses a long-lived develop branch alongside main, with feature branches and release or hotfix branches around them. In AWS’s description, approved feature branches merge into develop, and a release branch is then created for upper environments. This gives a team explicit release-management branches, but persistent branches require coordination and synchronization.
feature branches → develop → release branch → main
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GitHub Flow: short branch, merge, deploy
GitHub describes GitHub Flow as a lightweight, branch-based workflow for teams and projects that deploy regularly. A change is developed on a short-lived feature branch, reviewed, and merged into main. The model assumes the team can deploy after that merge.
Rank #4
main → short-lived feature branch → review → main → deploy
That assumption matters: if a merge cannot normally be deployed, the team needs to account for its release gates or use a workflow with explicit promotion stages. GitHub Flow’s simplicity does not itself provide separate release lines.
GitLab Flow: feature work with issue tracking and optional stages
GitLab describes GitLab Flow as combining feature-driven development with issue tracking and continuous delivery. Work can be developed against main; where staged promotion is needed, the workflow can add branches such as production, stable, or pre-production branches.
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feature branch → main → test/acceptance → production
The exact branch arrangement depends on the project’s deployment path. GitLab Flow can model test, acceptance, production, or stable stages; teams need not add environment branches when their deployment process does not need them.
When should a team use release branches?
A release branch is useful when software must be released externally and maintained separately from ongoing development. GitLab recommends creating a stable branch from main as late as possible. Once announced, that branch should accept only serious fixes. Where possible, make a fix on main first and then cherry-pick it to the release branch, so the correction is not stranded in the older release line.
main → stable release branch → release fixes
fix on main → cherry-pick to release branch
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| Workflow or family | Best fit | What to watch |
|---|---|---|
| Centralized | Small projects or projects with few updates | Concurrent changes share one branch with less isolation. (GitLab overview) |
| Feature branching | Parallel feature or fix work with review before merge | Branch lifetime, divergence, and merge volume. (GitLab overview) |
| Trunk-based development | Frequent integration and continuous or regular delivery | Requires frequent integration, automated tests, and CI to keep the trunk releasable. (AWS Prescriptive Guidance) |
| Personal branching | Isolating individual work before it is shared | Coordination and integration work can grow with the team. (GitLab overview) |
| Forking | Contributions from people without direct write access to the canonical repository | Contributors submit changes upstream from separate forks. (GitLab overview) |
| GitHub Flow | Teams that deploy regularly after merging reviewed work into main |
Its lightweight model assumes deployment can follow the merge. (GitHub Docs; AWS Prescriptive Guidance) |
| GitLab Flow | Feature-driven work with issue tracking and optional environment or stable branches | Choose branches only for stages or stable lines the delivery process needs. (GitLab documentation) |
| GitFlow | Teams that want explicit release management around scheduled releases | Long-lived branches add coordination and synchronization. (AWS Prescriptive Guidance; GitLab documentation) |
| Release branches | Externally released versions maintained separately | Cut the stable branch late and keep fixes synchronized with main where possible. (GitLab documentation) |
How to choose a branching strategy
- Start with deployment cadence. If the team deploys regularly and can deploy after a merge to
main, GitHub Flow is a lightweight fit. If frequent integration and continuous releasability are the priority, consider trunk-based development. - Check how many versions must stay supported. If the team maintains an externally released version separately from current development, plan for a stable or release branch. If it supports only one current line, a simpler workflow avoids that extra branch coordination.
- Match branches to real delivery gates. If code moves through test, acceptance, production, or stable stages, GitLab Flow can represent those stages with optional branches. Do not add persistent branches without a stage or release line they serve.
- Assess CI and test maturity. Trunk-based development relies on frequent integration and automated testing to keep the trunk releasable. Where those practices are not dependable, first address that constraint or choose a workflow whose release management matches the team’s current process.
- Account for contributor permissions. Use a forking workflow when outside contributors should propose changes without write access to the canonical repository. For work within a team, feature branches provide a separate branch per change without requiring separate repository forks.
- Keep branches no longer-lived than necessary. Short-lived branches limit divergence; persistent develop, stable, or release branches can serve release management, but require explicit ownership and synchronization.
What is the practical difference between GitFlow and trunk-based development?
They make different trade-offs around integration and release management. Trunk-based development brings changes into one shared trunk frequently and relies on CI and automated tests to keep it releasable. GitFlow keeps develop alongside main and uses feature, release, and hotfix branches to organize work around releases. The former favors frequent integration; the latter makes release structure explicit, at the cost of more branches to coordinate.
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