Open Source The StoryGraph Alternatives
A curated collection of the 1 best open source alternatives to The StoryGraph.
The best open source alternative to The StoryGraph is BookWyrm. If that doesn't suit you, we've compiled a ranked list of other open source The StoryGraph alternatives to help you find a suitable replacement.
The StoryGraph alternatives are mainly Media & Streaming. Browse these if you want a narrower list of alternatives or looking for a specific functionality of The StoryGraph.
Federated social network for tracking reading, reviewing books and following friends, run as small self-governed instances that reach Mastodon.
BookWyrm is a social network for tracking your reading, talking about books, writing reviews and working out what to read next. Rather than one monolithic service in the shape of Goodreads, it is meant to be run as small, self-determining communities: a book club, a group of friends, or a server devoted to one corner of literature.
Federation comes from ActivityPub. An instance interoperates with other BookWyrm servers and with other ActivityPub software such as Mastodon, so a friend posting from Mastodon can read and comment on a review published on your instance. Federation also shares metadata about books and authors, which builds a decentralized book database collaboratively.
The feature set stays close to what a reading community needs.
- Posts about books: reviews, comments on current reading and quotes, in conversation with the wider network.
- Reading activity: a record of what you have finished and what you intend to read next.
- Moderation: administrators pick which instances to federate with, and users control who sees their posts.
- Django backend: PostgreSQL for storage, with Celery and Redis for task queuing and activity streams.
- Front end: Django templates, the Bulma CSS framework and vanilla JavaScript used in moderation.
- Deployment: Docker Compose with Gunicorn, Nginx and Flower for watching Celery.
The documentation site carries separate instructions for a developer environment and a production install. The project is explicit about welcoming human contributors at any experience level, and equally explicit that AI-generated code and content are not accepted.
