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Running PhotoPrism on a Synology NAS

Should you experience problems with the installation, we recommend that you ask the Synology community for advice, as we cannot provide support for third-party software and services.

Visit the Synology Knowledge Base to learn what kind of CPU and how much memory your device has. We recommend hosting PhotoPrism on a 64-bit system with at least 2 cores and 3 GB of physical memory. High-resolution panoramic images may require additional swap space and/or physical memory above the recommended minimum.

RAW image conversion and TensorFlow are disabled on devices with 1 GB or less memory. You will have to resort to 32-bit Docker images to run PhotoPrism and MariaDB on ARMv7-based entry-level devices like the Synology DS218j.

Indexing large photo and video collections significantly benefits from local SSD storage and plenty of memory for caching. Especially the conversion of RAW images and the transcoding of videos are very demanding. We take no responsibility for instability or performance problems if your device does not meet the requirements.

Setup using Docker

The Synology user interface has been updated in the meantime, so the screenshots from the tutorial below may be outdated. Also, we recommend using mariadb instead of SQlite.

Since we don't have a Synology test device, contributions to a step-by-step tutorial are greatly appreciated. You can contribute by clicking to send a pull request with your changes.

You can follow these instructions to install PhotoPrism on your Synology NAS:

Will my device be fast enough?

This largely depends on your expectations and the number of files you have. Most users report that PhotoPrism runs well on their Synology NAS. However, you should keep in mind:

  • initial indexing may take longer than on standard desktop computers
  • the hardware has no video transcoding support and software transcoding is generally slow


If your device runs out of memory, the index is frequently locked, or other system resources are running low:

Other issues? Our troubleshooting checklists help you quickly diagnose and solve them.

Help improve these docs! You can contribute by clicking to send a pull request with your changes.