Batch Resize vs Cantaloupe
Batch Resize
batchresize.comCantaloupe
cantaloupe-project.github.ioSide by side
| Figure | Batch Resize | Cantaloupe |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| macOS | Yes | — |
| iOS | Yes | — |
| Self-hosted | — | Yes |
| Plans published | 2 | 1 |
| Spec score · Photo Resizing Software | 8.0 (#8) | 7.9 (#10) |
| Purpose | Batch Resize resizes multiple images to a chosen pixel size. | Cantaloupe is an open-source dynamic image server that generates image derivatives on demand from high-resolution source images. |
| Support | The App Store listing links to the developer’s privacy policy and website. | The project directs questions and comments to GitHub Discussions and bug reports or feature requests to GitHub Issues. |
Plans
In their own words
Batch Resize
Batch Resize is an iOS and macOS app for changing multiple images to a chosen pixel size. Its current App Store listing says it can resize up to 500 images at once. Users can choose fixed width, fixed height, maximum pixel, aspect fill or aspect fit, then save results to Camera Roll or a custom album. Maximum output dimensions are 4000 × 4000 pixels on 32-bit devices and 8000 × 8000 pixels on 64-bit devices. The listing names English, Dutch, French, German, Italian, Japanese, Korean, Portuguese, Russian, Simplified Chinese and Spanish. Batch Resize is free to download and contains advertising; a 34.99 USD once in-app purchase removes ads. The developer indicates usage data may be used to track users and collected for third-party advertising and analytics, though Apple says this disclosure has not been verified by Apple.
Cantaloupe
Cantaloupe is a free, open-source, self-hosted image server that creates derivatives from high-resolution sources when requested. It can crop, scale, and rotate images for deep-zoom viewers and on-demand thumbnails, and conforms to every IIIF Image API version through 3.0. Sources may be filesystems, HTTP or HTTPS servers, S3, Azure Storage, or relational database BLOBs. Processing choices include Java 2D, JAI, TurboJPEG, Kakadu, OpenJPEG, Grok, FFmpeg, and PDFBox. Caches can use filesystem, Java heap, JDBC, S3, Azure Storage, or Redis implementations. Security options include selective image and text watermarking, image-region redaction, HTTPS, HTTP Basic authentication, and customizable authorization policies. Configuration uses environment variables or a .properties file, with most changes applying without restart. Java 17 is required at minimum. The project says no official Docker image is currently available.