Monorepos vs. Polyrepos: Which one fits your use case?

Monorepos centralize all codebases in one repository, making cross-service changes atomic, dependency management centralized, and tooling consistent. They work best when teams need tight coordination and shared practices. Polyrepos isolate services into separate repositories for independent deployments, varied tech stacks, and simplified ownership boundaries. Polyrepos are ideal for teams operating autonomously.

When choosing between monorepos and polyrepos, the right choice depends on whether you’re optimizing for integration or independence.

Repository structure and ownership boundaries

Monorepos consolidate all services and libraries into a single versioned repository. This structure allows changes across multiple packages or services to be atomic. A developer updating an API schema and its corresponding client libraries can do so in one commit, tracked in one PR, reviewed by a single team. Ownership boundaries are defined through folder structure, codeowners files, and service-specific tooling — not separate repositories.

Polyrepos, on the other hand, enforce boundaries at the repository level. Each service, library, or application lives in isolation, often with its own CI pipeline, issue tracker, and versioning strategy. This decoupling simplifies mental models for single-purpose teams, particularly when external contributors or third-party service owners are involved. It also makes it easier to deprecate services without bleeding code across unrelated components.

Dependency management and versioning

Monorepos standardize dependency versions using centralized tooling. In a JavaScript or TypeScript workspace, tools like pnpm or turborepo resolve internal packages in-place, meaning a shared library used by ten services only needs to be built once. Services can consume the latest commit of the internal library, or use tools like Changesets for version tagging and changelog generation within the repo.

In polyrepos, dependency boundaries are enforced through published packages. You must publish a shared library to a package registry, then bump and install the new version in downstream consumers. This decoupling adds friction but increases reliability, as consumers are insulated from upstream changes unless they explicitly opt in.

CI/CD pipeline

CI pipelines in monorepos benefit from tools that support change detection. With Nx, Bazel, or GitHub Actions and custom path filters, it’s possible to run tests only for services impacted by a commit. This enables fast iteration across multiple parts of the system. However, without careful cache management and tooling enforcement, pipeline duration can inflate as the repository grows.

Polyrepos use independent pipelines, so a failing test in Service A won’t block the deployment of Service B. Each pipeline is tailored to the service’s requirements, and CI durations remain short even as the number of repositories scales. But cross-repo integration tests become harder to manage, requiring either a synthetic monorepo for integration CI or a dedicated test orchestration system that can clone and build multiple repositories simultaneously.

Code reviews and refactoring

Monorepos enable coordinated refactors. You can rename a core type, update all references across services, and ship everything together. Linting, formatting, and testing configurations are shared across the codebase, enforced by a unified toolchain. This consistency enforces architectural guidelines and simplifies onboarding.

Polyrepos make refactoring slower. Each change must be tracked across repositories, reviewed separately, and released in stages. Linter configurations may drift, resulting in style mismatches or outdated tooling. On the other hand, polyrepos support more varied tech stacks. A Go backend team and a React frontend team can evolve independently without the friction of shared config or conflicting dependencies.

Tooling and build systems

Monorepos centralize tooling. A new developer pulls the repository, runs a bootstrapping script, and gains access to every service and library. Tooling can be unified across the repo using a single CLI entry point, whether that’s a shell script, a Makefile, or a framework-specific command. This approach reduces the cost of context switching but increases initial setup time and disk usage. A large codebase like that can be overwhelming for beginners or new team members.

Polyrepos are lighter to clone and faster to understand individually. Tooling lives in each repository and can be tightly scoped. However, inconsistencies accumulate. Two services might use different versions of a CLI tool or different deployment strategies, requiring new hires to internalize multiple practices and switch environments frequently.

Choosing based on coordination and autonomy

If your teams frequently make cross-service changes, rely on shared libraries, or need tight coordination for feature releases, monorepos eliminate friction. If your teams are independent, ship at their own pace, and value decoupling over tight integration, polyrepos are a better fit. Consider whether your organizational bottlenecks stem from code coordination or team autonomy, then choose accordingly.

Choosing based on project requirements

Teams prioritizing fast iteration and shared ownership benefit from monorepos. Organizations that need strict isolation, independent versioning, or decentralized teams should lean toward polyrepos. Hybrid approaches, such as grouping related services in a monorepo while keeping others separate, offer a good middle ground.

The decision between monorepos vs. polyrepos hinges on team size, deployment cadence, and dependency coupling. Neither approach is universally superior; each imposes tradeoffs in tooling, workflow, size, and maintainability. To ensure you get the right fit, evaluating these factors against project requirements ensures the right fit.

The table below tells you which repository model to pick based on the aspect you’re optimizing for:

Monorepo architecture example

Below is a practical monorepo setup using pnpm, TurboRepo, and a shared TypeScript config. All services and libraries live in a single version-controlled repository:

repo/
├── apps/
│   ├── api/
│   │   ├── src/
│   │   └── package.json
│   ├── admin/
│   │   ├── src/
│   │   └── package.json
│   └── web/
│       ├── src/
│       └── package.json
├── packages/
│   ├── ui/
│   │   ├── components/
│   │   └── package.json
│   └── config/
│       ├── eslint/
│       └── tsconfig/
├── .github/workflows/ci.yml
├── turbo.json
├── pnpm-workspace.yaml
└── package.json

In this example, dependency resolution is handled through pnpm workspaces. Internal packages are linked automatically. The build and test orchestration is done via TurboRepo, which detects changes and scopes commands, while code ownership is enforced via CODEOWNERS and scoped directories under apps/. Finally, shared tooling lives in packages/config, which can include ESLint, Prettier, or TS configs.

To build only changed apps, run the following:

turbo run build --filter=...  # Turbo handles caching and change detection

And run this to run all tests:

turbo run test

Polyrepo architecture example

Each service is its own Git repository with a separate CI pipeline. Internal libraries are published to a registry (e.g., npm or GitHub Packages).

Repo: api-service

api-service/
├── src/
├── package.json
├── .github/workflows/ci.yml
└── .env

Repo: web-client

web-client/
├── src/
├── package.json
├── .github/workflows/ci.yml
└── .env

Repo: shared-ui

shared-ui/
├── components/
├── package.json
└── .github/workflows/publish.yml

In this code, shared-ui is versioned and published to npm or a private registry on each main merge. api-service and web-client install @org/shared-ui@^1.2.0 via npm install. Each repo runs its own pipeline, and PRs are reviewed and merged independently, while releases are tracked using tags and changelogs in each repository.

Conclusion

The decision between monorepos vs. polyrepos depends on whether you’re optimizing for the scale of services or the speed of autonomy. A monorepo setup pays off when coordination between teams is high and tight integration between services or libraries is critical. Polyrepos work better when services evolve independently, and coordination overhead must be avoided.

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