When using Spatie's translation system, specifically the spatie/laravel-translatable package, there are several performance considerations to keep in mind:
- Storage Format and Querying: The package stores translations as JSON columns in the database. This approach avoids creating multiple columns for each language, which can simplify schema management and improve write performance. However, querying and sorting by JSON fields can be more complex and slower compared to traditional relational columns. Sorting on JSON columns is particularly more labor-intensive and may lead to slower queries[1].
- Search Performance: If your application requires frequent full-text searches on translated content, Spatie's JSON-based translation storage might not be optimal. Some users have reported that for stable datasets like product information or SEO attributes, using a separate translation table per language (one row per language) can enhance search performance. This method allows easier fallback to default locales and better indexing strategies[1].
- Scalability and Maintenance: While the JSON approach is user-friendly and works well for many use cases, it might become cumbersome when dealing with large datasets or when you need advanced translation management features such as tracking untranslated labels, approval workflows, or reusing translations. In such cases, a more normalized database schema might be preferable[1].
- Autocomplete and UI Concerns: Some developers have noted issues with autocomplete features when using Spatie's package, especially when languages overlap in certain string segments, leading to irrelevant suggestions. This is more of a user interface consideration but can affect perceived performance and usability[1].
- Caching and Optimization: For related Spatie packages like laravel-data, performance can be improved by caching analysis results before deployment, ensuring pre-analyzed data objects are used in production. While this is not directly about the translation package, it reflects a general approach to optimize Spatie packages[3].
- Community Feedback: Many users report no significant performance issues for typical use cases involving multiple languages (e.g., 5-7 languages). The package is praised for its simplicity and ease of use. However, for complex or large-scale applications, custom solutions or alternative packages might be considered[1][4].
In summary, Spatie's translation system performs well for many applications, especially when the number of languages is moderate and the dataset is not extremely large. The main performance trade-offs come from using JSON columns for translations, which can complicate sorting and searching. For heavy search or complex translation workflows, alternative database schemas or packages might be more efficient.
These considerations should guide your choice based on your application's specific needs and scale.
Citations:
[1] https://www.reddit.com/r/laravel/comments/1j3613p/pros_and_cons_by_using_spatietranslatable/
[2] https://github.com/spatie/laravel-data/discussions/713
[3] https://spatie.be/docs/laravel-data/v4/advanced-usage/performance
[4] https://laracasts.com/discuss/replies/934789
[5] https://github.com/Laravel-Backpack/CRUD/issues/67
[6] https://www.sciencedirect.com/science/article/pii/S2215016119302717
[7] https://freek.dev/593-a-laravel-package-to-store-language-lines-in-the-database
[8] https://stackoverflow.com/questions/74787886/is-there-a-reason-why-the-spatie-package-laravel-tags-has-no-down-function-in