InfDB - Energy and Infrastructure Database provides a modular and easy-to-configure open-source data and tool infrastructure. It is equipped with essential services, designed to minimize the effort required for data management. We follow a platform-independent containerized approach that streamlines collaboration in energy modeling and analysis, empowering the growth of an ecosystem by offering standardized interfaces and APIs, and by allowing users to dedicate their focus to generating insights rather than handling data logistics.

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• Why use it?
• How it works?
• Getting Started
• License and Citation

InfDB addresses common challenges in energy system modeling and analysis, particularly those related to data management. By providing a standardized and modular infrastructure, InfDB reduces the time and effort required to set up and maintain data systems. This allows researchers, analysts, and planners to focus on their core tasks of modeling and analysis, rather than being bogged down by data logistics.

InfDB can be used effectively wherever geospatial and time series information is required. Possible applications include:

• Energy System Modeling
• Municipal Heat Planning and Infrastructure Planning
• Scenario and Geospatial Analysis

InfDB consists of the following layers:

• Services – Dockerized open-source software providing base functionality.
• Tools – Software interacting with InfDB.
• Python API – Python package pyinfdb for interacting with InfDB.

The InfDB platform provides a suite of essential services designed to facilitate database operation and administration, data handling and visualization, and connectivity. Each preconfigured service can be activated individually to tailor the environment to your specific requirements.

More information, a list of available services see Services.

Tools are software that interact with InfDB and process data through standardized, open interfaces. This modular approach allows you to tackle problems of any complexity by combining different tools into custom toolchains.

More information, a list of integrated tools and additional information, see Tools.

If you want to use the InfDB with the default settings just use the Quick Start below. For more information in detail read the Usage Guide of the official documentation.

• Docker Engine: https://docs.docker.com/engine/install/
• Docker Desktop: https://docs.docker.com/desktop/

The InfDB allows a modular folder structure to manage multiple database instances independently. Each instance represents a separate deployment with its own data, configuration, and services—ideal for handling different regions, projects, or environments.

infdb/
├── infdb-demo/
├── muenchen/
├── bavaria/
├── grid-planning/
└── ...

The recommended structure places all instance data in docker managed volumes while keeping each instance's configuration and tools in separate directories (e.g. by region muenchen/, bavaria/). This approach simplifies backups, migrations, and multi-instance management.

The configuration of services is managed through environment variables set in the environment file .env and for data import in the YAML file configs/config-infdb-import.yml. The environment file controls which services are activated and their settings, while the YAML file specifies which datasets are imported and how they are processed. If no configuration is provided, the InfDB will create an environment file as well as a YAML file with default settings. More details can be found in section Setup of the documentation.

Default configuration settings and the database service activated:

# ==============================================================================
# SERVICE ACTIVATION
# ==============================================================================
# Select profiles to activate
COMPOSE_PROFILES=db  # db,admin,notebook,qwc,api

# ==============================================================================
# POSTGRESQL DATABASE (Db Service)
# ==============================================================================
# Profile: db

# Database name
SERVICES_POSTGRES_DB=infdb

# Database credentials
SERVICES_POSTGRES_USER=infdb_user
SERVICES_POSTGRES_PASSWORD=infdb

# Host:Port address from which a container is able to reach the Postgres database
SERVICES_POSTGRES_HOST=host.docker.internal
SERVICES_POSTGRES_EXPOSED_PORT=54328

# EPSG code for spatial reference system (25832 = ETRS89 / UTM zone 32N)
SERVICES_POSTGRES_EPSG=25832

You can quickly start InfDB with default configuration and credentials as mentioned above by following these steps:

First of all, create the main infdb directory and navigate into it:

mkdir infdb
cd infdb

# Replace "infdb-demo" by name of instance 
git clone --recurse-submodules git@github.com:tum-ens/InfDB.git infdb-demo
cd infdb-demo

bash infdb.sh start

bash infdb.sh import

bash infdb.sh stop

Once InfDB has been successfully started and data has been imported, you can use the integrated tools or develop your own using the provided tool framework to interact with InfDB data. Detailed information on available tools and their usage is provided in the Tools section of the documentation.

To run the Linear Heat Density demo, execute:

uv run python3 tools/tools.py -p linear

Additional information is available in the Linear Heat Density section of the documentation.

The code of this repository is licensed under the Apache 2.0 License.
See LICENSE for rights and obligations. See Citation for citation of this repository.
Copyright: TU Munich - ENS | Apache 2.0 License

Patrick Buchenberg

Chair of Renewable and Sustainable Energy System Technical University of Munich (TUM) Email: patrick.buchenberg@tum.de https://www.epe.ed.tum.de/ens/staff/ensteam/patrick-buchenberg/