Choosing a Private Maven Repository for Your Spark Scala Team in 2026

Most comparison guides for artifact repositories are written for Java teams using Maven or Gradle. If your team builds Spark Scala applications with sbt, the landscape looks different — and some popular options have sharp edges that only show up with sbt's dependency resolution.

Why You Need a Private Repository

Once your Spark Scala team grows beyond a couple of people, you'll hit the point where shared internal libraries make sense — common UDF collections, custom connectors, standardized schemas, test utilities. Publishing these to Maven Central doesn't make sense for internal code, and passing JARs around manually is a path to version confusion.

A private Maven repository gives you:

• Controlled publishing — push internal artifacts with standard sbt publish and resolve them like any other dependency
• Proxy caching — mirror Maven Central and other public repositories behind a single endpoint, cutting external network calls and protecting against upstream outages
• Access control — restrict who can publish and consume your team's artifacts

The proxy caching piece matters more than most teams realize. If your CI builds resolve Spark's transitive dependency tree from Maven Central on every run, you're making hundreds of HTTP requests per build. A local proxy cache turns those into fast local reads after the first fetch.

The Contenders

Here's how the main options stack up for Scala teams using sbt.

Sonatype Nexus Community Edition — Free, Self-Hosted, Full-Featured

Nexus Community Edition is the option most teams should evaluate first. It's free, supports Maven repositories natively, and handles proxy caching out of the box.

What you get:

• Maven, npm, PyPI, NuGet, and more — broad format support
• Proxy repositories that cache upstream sources like Maven Central
• Group repositories that combine proxy and hosted repos behind a single URL
• SSO/SAML authentication
• CI/CD integration with Jenkins, GitHub Actions, GitLab CI/CD
• High availability and cloud deployment (Azure, GCP, AWS)
• No storage or transaction limits

sbt configuration is standard:

// build.sbt — resolve from Nexus
resolvers += "Internal" at "https://nexus.yourcompany.com/repository/maven-releases/"

// Publish to Nexus
publishTo := Some("Internal" at "https://nexus.yourcompany.com/repository/maven-releases/")

// Credentials in ~/.sbt/1.0/credentials or environment variables
credentials += Credentials(Path.userHome / ".sbt" / "1.0" / ".credentials")

Nexus works with sbt's default Coursier resolver and Ivy fallback without any special plugins. This is a bigger deal than it sounds — as you'll see below, some cloud options don't.

The trade-off: You're running and maintaining the server yourself. That means infrastructure, backups, and upgrades. For a team that already manages internal services, this is negligible. For a small team without ops capacity, it's overhead.

Cost: Free. No strings attached. The paid Nexus Repository Pro adds enterprise support with SLAs and advanced security scanning, but the free edition covers artifact hosting and proxying completely.

JFrog Artifactory — Enterprise-Grade, Enterprise-Priced

Artifactory is the most feature-complete option. It supports 50+ package formats, has the best proxy and caching layer, and comes with enterprise security scanning, container registries, and federated replication.

For sbt, it works cleanly. Artifactory has native Maven repository support, handles Coursier resolution without issues, and provides the broadest upstream proxy support.

The problem is cost. Artifactory's pricing puts it out of reach for most small and mid-size teams:

SaaS storage overage runs $0.75–$1.25/GB depending on volume. Spark's transitive dependency tree is large — a proxy cache for a team building Spark applications will consume non-trivial storage.

When it makes sense: If your organization already has an Artifactory license for other teams (Java, Python, Docker), adding your Spark Scala project to it is easy and the cost is amortized. If you're buying Artifactory specifically for a Spark Scala team, Nexus Community Edition gives you everything you need for free.

GitHub Packages — Simple, But Limited

GitHub Packages is convenient if your code already lives on GitHub. Publishing and resolving Maven artifacts works through the GitHub API, and authentication uses the same tokens your CI already has.

The sbt-github-packages plugin handles the sbt integration:

// project/plugins.sbt
addSbtPlugin("com.codecommit" % "sbt-github-packages" % "0.5.3")

// build.sbt
githubOwner := "your-org"
githubRepository := "your-repo"
githubTokenSource := TokenSource.Environment("GITHUB_TOKEN")

// Resolve from any repo in your org
resolvers += Resolver.githubPackages("your-org")

The limitations are significant for Spark teams:

• No proxy caching. GitHub Packages is a hosted registry, not a repository manager. Every transitive dependency still resolves from Maven Central. You get no caching benefit for CI builds.
• 500 MB storage on free plans. Shared with GitHub Actions artifacts. The Team plan ($4/user/month) bumps this to 2 GB. Overages are $0.25/GB/month. Spark artifacts with shaded dependencies can be large.
• Maven-style only. Ivy-style publication silently fails. The sbt plugin explicitly blocks it, but this is a footgun if you're not aware.
• Authentication quirks. Despite what the docs say, read access requires a write:packages scope token in practice, not just read:packages.

When it makes sense: Small teams with a handful of lightweight internal libraries, minimal CI build frequency, and everything already on GitHub. Not a good fit if proxy caching or build performance matters.

AWS CodeArtifact — Good sbt Support, Pay-Per-Use

AWS CodeArtifact is a managed repository service with Maven support, upstream proxying, and IAM-based authentication. For teams already deep in AWS, it's a natural fit.

Pricing is consumption-based:

The free tier covers a small team's needs. A medium-sized team with regular CI builds might spend $5–15/month — far less than Artifactory and with no infrastructure to manage.

sbt integration works through community plugins. The most established was sbt-codeartifact, which handled authentication via the AWS SDK's DefaultCredentialsProvider — meaning IAM roles, environment variables, and credential files all worked automatically. That plugin is now archived, but alternatives like sbt-aws-code-artifact provide similar functionality with automatic credential refresh.

// project/plugins.sbt
addSbtPlugin("io.github.bbstilson" % "sbt-codeartifact" % "0.2.1")

// build.sbt
codeArtifactUrl := "https://your-domain-123456789.d.codeartifact.us-east-1.amazonaws.com/maven/your-repo/"

The upstream proxy is the key feature. CodeArtifact can proxy Maven Central, reducing external calls and giving you a cached copy of everything your builds resolve. Combined with IAM authentication, this gives you proxy caching without running your own Nexus instance.

When it makes sense: Teams running Spark on EMR, EKS, or other AWS infrastructure where IAM authentication is already in place. The pay-per-use model keeps costs predictable for small teams and scales without operational overhead.

The Options to Avoid (for sbt)

Not every Maven-compatible repository works well with sbt. Two popular options have known, long-standing issues.

Google Artifact Registry

Google Artifact Registry supports Maven, but Coursier — sbt's default dependency resolver since sbt 1.3 — does not support Google Artifact Registry authentication. That issue has been open since 2021 with no resolution.

The workaround is setting useCoursier := false in your build, which forces sbt back to the Ivy resolver. This works, but Coursier is significantly faster than Ivy resolution — disabling it for your entire build to accommodate your repository is a bad trade-off. Alternative plugins like sbt-gcs-resolver and gar-handler attempt to bridge the gap with Coursier support, but they add complexity and may lag behind Coursier updates.

Unless you have a strong organizational mandate to use Google Cloud for everything, pick a repository that works with sbt out of the box.

Azure Artifacts

Azure Artifacts has a documented issue where sbt publish fails with HTTP 203 responses instead of proper success or error codes. Azure's server returns an HTML login page instead of the expected Maven response when it receives requests from sbt's HTTP client. The root cause appears to be user-agent sniffing — setting the user-agent to Apache Maven/3.6.3 makes it work, but that's a fragile hack.

Resolution from Azure Artifacts also has authentication issues documented across multiple sbt GitHub issues. If your organization uses Azure DevOps, consider running Nexus Community Edition alongside it for your Maven repositories rather than fighting with Azure Artifacts' sbt compatibility.

Decision Framework

Here's a practical framework for choosing, based on team size and infrastructure:

Self-hosted infrastructure available → Nexus Community Edition. Free, full-featured, works perfectly with sbt. If you have someone who can run a Docker container or VM, this is the simplest answer. You get proxy caching, access control, and support for every package format your team might need.

AWS-native team, no ops appetite → AWS CodeArtifact. Managed service, pay-per-use pricing, IAM authentication, and upstream proxying. The community sbt plugins work well. Good default for teams that want proxy caching without running their own infrastructure.

Enterprise with existing JFrog license → Artifactory. If the license already exists, use it. Don't buy one specifically for a Spark Scala team.

Small team, everything on GitHub, few internal libs → GitHub Packages. Convenient for simple cases. Outgrow it when you need proxy caching or when storage limits become a constraint.

Google Cloud or Azure → Nexus Community Edition. The native artifact services on these clouds have sbt compatibility issues that will cost you more time than they save. Run Nexus in a container on your cloud of choice and sidestep the tooling friction entirely.

Proxy Configuration: The Part Most Teams Skip

Whichever repository you choose, configure upstream proxy caching if your option supports it (Nexus, Artifactory, and CodeArtifact do; GitHub Packages does not).

The setup in sbt is simple — point your resolvers at your repository manager instead of Maven Central:

// build.sbt — route all resolution through your repository manager
resolvers := Seq(
  "Internal Releases" at "https://nexus.yourcompany.com/repository/maven-releases/",
  "Internal Snapshots" at "https://nexus.yourcompany.com/repository/maven-snapshots/",
  "Maven Central Proxy" at "https://nexus.yourcompany.com/repository/maven-central/"
)

// Or use a group repository that combines all three
resolvers := Seq(
  "All Repositories" at "https://nexus.yourcompany.com/repository/maven-public/"
)

// Optional: block direct access to Maven Central
externalResolvers := Resolvers.noDefaultResolvers

This matters for Spark projects specifically because Spark's dependency tree is enormous. Even with Spark dependencies in provided scope, a typical Spark SQL dependency pulls in hundreds of transitive artifacts. Without a proxy cache, every CI run re-downloads all of them from Maven Central. With a proxy cache, the first build populates the cache and subsequent builds resolve locally.

The proxy also protects against dependency confusion attacks, where an attacker publishes a higher-versioned package to Maven Central with the same coordinates as your internal library. A proxy repository with priority rules ensures internal artifacts always win.

Summary

For most Spark Scala teams, the choice comes down to Nexus Community Edition (free, self-hosted, full-featured) or AWS CodeArtifact (managed, cheap, good sbt support). Artifactory is the right answer only if someone else is paying for it. GitHub Packages works for simple cases but lacks the proxy caching that makes a real difference for Spark build performance.

Whatever you pick, make sure it works with Coursier and supports upstream proxy caching. Those two features matter more than anything else for sbt-based Spark projects.