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Eclipse Dataspace Connector


The Eclipse Dataspace Connector provides a framework for sovereign, inter-organizational data exchange. It will implement the International Data Spaces standard (IDS) as well as relevant protocols associated with GAIA-X. The connector is designed in an extensible way in order to support alternative protocols and integrate in various ecosystems.

Please also refer to:

Built with

One of the guiding principles in developing the connector is simplicity and keeping the core small and efficient with as little external dependencies as possible to avoid version conflicts. We do not want to force any third-party dependencies onto our users, so we aim to avoid any of the big frameworks. Of course, if you want to use them, you still can add them to your extensions (see: [TBW]). The connector is a plain Java application built with Gradle, but it can be embedded into any form of application deployment.

For detailed information about the project, please have a look at our documentation.

Getting Started

Add Maven dependencies

Official versions are available through MavenCentral . Please add the following instructions in your build.gradle[.kts] file (if not already present):

repositories {
    // ... other maven repos

We strongly recommend to use official versions and only switch to snapshots if there is a clear need to do so, or you've been instructed to do so, e.g. to verify a bugfix.

All artifacts are under the org.eclipse.dataspaceconnector group id, for example:

dependencies {
    // any other dependencies

Using SNAPSHOT versions

In addition, EDC regularly publishes snapshot versions, which are available at Sonatype's snapshot repository. In order to add them to your build configuration, simply add this:

repositories {
    maven {
        url = uri("")
    // any other repos

Then you can add snapshot dependencies by simply using the -SNAPSHOT version suffix:

dependencies {
    // any other dependencies

A comprehensive list of all available modules can be found here. This file will always list the most recent snapshot version, please check MavenCentral for official versions.

Please be aware of the following pitfalls:

  • snapshots are by definition unstable - every new snapshot replaces an old one
  • this may cause unrepeatable builds
  • snapshots are created irregularly, we do not have any fixed publish schedule

Using release versions

We plan to have actual release versions starting some time mid 2022. Please check back soon.

For more information about versioning please refer to the release documentation

Checkout and build from source

The project requires JDK 11+. To get started:

git clone

cd DataSpaceConnector

./gradlew clean build

That will build the connector and run unit tests.

[Optional] Setup your IDE

If you wish to configure your IDE/editor to automatically apply the EDC code style, please follow this guide.

Note: the style guide will be checked/enforced in GitHub Actions.

Run your first connector

Connectors can be started using the concept of "launchers", which are essentially compositions of Java modules defined as gradle build files.

It is expected that everyone who wants to use the EDC will create their own launcher, customized to the implemented use cases.

There is an ids-connector launcher, which launches a simple connector that has no cloud-based extensions. However, it needs an IDS certificate and a running DAPS. So make sure to take a look at this guide first.

Then run

./gradlew :launchers:ids-connector:shadowJar
java -jar launchers/ids-connector/build/libs/dataspace-connector.jar

Once it says "Dataspace Connector ready" the connector is up and running.

More information about the extension concept can be found here [TBW].

More information about shadowJar can be found here.

Generate the OpenApi specification

Please refer to this document.

Directory structure


This is the primary extension point for the connector. It contains all necessary interfaces that need to be implemented as well as essential model classes and enums. Basically, the spi modules defines the extent to what users can customize and extend the code.


Contains all absolutely essential building that is necessary to run a connector such as TransferProcessManager, ProvisionManager, DataFlowManager, various model classes, the protocol engine and the policy piece. While it is possible to build a connector with just the code from the core module, it will have very limited capabilities to communicate and to interact with a data space.


This contains code that extends the connector's core functionality with technology- or cloud-provider-specific code. For example a transfer process store based on Azure CosmosDB, a secure vault based on Azure KeyVault, etc. This is where technology- and cloud-specific implementations should go.

If someone were to create a configuration service based on Postgres, then the implementation should go into the extensions/database/configuration-postgres module.


Launchers are essentially connector packages that are runnable. What modules get included in the build (and thus: what capabilities a connector has) is defined by the build.gradle.kts file inside the launcher subdirectory. That's also where a Java class containing a main method should go. We will call that class a "runtime" and in order for the connector to become operational the runtime needs to perform several important tasks (="bootstrapping"). For an example take a look at this runtime


Contains a Helm chart for the EDC runtime. You can use the launchers/generic/Dockerfile to build a runtime image for your connector runtime, and deploy the resulting image to Kubernetes.


Contains implementations for communication protocols a connector might use, such as IDS.


Contains code that demonstrates how the connector can be used in various scenarios. For example, it shows how to run a connector from a unit test in order to try out functionality quickly or how to implement an outward-facing REST API for a connector.


Contains utility code such as collection utils, string utils and helper classes.


Contains several scripts to deploy a connector in an AKS cluster on Microsoft Azure using Terraform.

Code style & Patterns

Please refer to the dedicated style guide and the patterns we documented in architecture principles.


See here for more information about project and milestone planning. Scheduled and ongoing milestones are listed here.


See how to contribute.


Available tags can be found here.