Our take
Activeregular commits and releases- Activity
- 63
- Community
- 44
- Issues
- 33
- Pull requests
- 69
+21 stars in the last 30 days
- Slower to close issues than 92% of the projects we track
Streamystats is an actively maintained, feature-rich Jellyfin companion, but its measured contributor concentration and slow issue closure make it important to plan for independent operation and support.
Good fit if
- You already run Jellyfin and want self-hosted analytics rather than a separate hosted service.
- You are comfortable deploying with Docker Compose and backing up the database before upgrades.
- You want optional AI search or recommendations, and can configure compatible embedding or chat providers if you enable them.
Look elsewhere if
- You need a project whose maintenance does not depend heavily on one contributor.
- You require quick issue resolution, since measured issue closure has been slow.
- You need a clearly stated license before evaluating or deploying the software. The supplied repository data does not specify one.
All health signals
| Last commit | 2026-09-13 (27 days ago) |
|---|---|
| Commits, last 90 days | 23 |
| Releases, last 12 months | 19 (latest v2.20.0, 2026-09-12) |
| Contributors | 26 (top contributor: 83% of commits) |
| Issues closed, last 90 days | 3 (typically closed in 248 days) |
| Pull requests merged, last 90 days | 23 (typically merged in 0 days) |
| Project age | 24 months |
Checked on 2026-10-11 with the GitHub API.
Project history
Daily GitHub snapshots since Oct 7, 2026. History covers stars and forks; health signals are not tracked historically.
Stars
849Forks
47Change since Nov 14, 2026: 0 stars·0 forks
Overview
Streamystats is a web-based analytics service for Jellyfin. It uses Jellyfin's API to turn viewing activity and library data into dashboards and statistics, so server owners and users can explore watch patterns beyond Jellyfin's built-in views.
It also offers optional AI chat and recommendations based on library embeddings. The project is aimed at people willing to run and maintain a separate service alongside Jellyfin, rather than users looking for a hosted analytics product.
Key Features
- Dashboard for overview statistics, live sessions, and recommendations.
- Per-user watch history and statistics, with support for multiple users and servers.
- Library, client, and watch-time statistics with filtering.
- Optional AI chat with library search and watch-related tools.
- Optional embedding-based recommendations, with explanations linking suggestions to watched items.
- Imports from Jellystat and the Playback Reporting Plugin to help bring in existing data.
- Docker Compose deployment and a setup wizard for connecting Jellyfin.
Use Cases
- Jellyfin server owners who want to see viewing trends and library statistics in one dashboard.
- Household users who want separate watch histories and recommendations for different accounts.
- Media enthusiasts deciding what to watch next based on their own viewing history and library.
- Existing Jellystat or Playback Reporting Plugin users who want to import data into a newer analytics service.
What you need
Detected in the repository
- Node.js (from package.json)
- A Compose file to run it with its related services
- Automated checks on GitHub Actions
Getting Started
The README recommends Docker Compose. After copying and configuring the repository's docker-compose.yml, including setting a random SESSION_SECRET, start the service with:
docker-compose up -d
Then open http://localhost:3000 and follow the setup wizard. See the README for configuration, versioning, and database backup guidance.
License in Plain Words
No standard license was detected. Without a license, the default copyright rules apply: you may read the code, but not reuse it. Check the repository or ask the authors.
Considerations
The project is active, with regular commits and releases, but most of the code comes from one person despite a broader contributor group. Issue handling is a notable concern: few issues were closed in the measured recent period, and the median time to close has been lengthy. The README also describes the project as a hobby project and warns that it may contain bugs.
Docker is the recommended deployment route, and the README warns that downgrading does not roll back database migrations. Back up the database before updates; restoring a backup is the documented rollback approach. AI chat and embeddings are optional and rely on OpenAI-compatible APIs when enabled. The supplied metadata does not identify a license, so verify the repository's current license before adopting or redistributing it.
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