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RepDB
RepDB is a one-time-purchase exercise dataset for developers building fitness and workout apps โ not a subscription, not a rate-limited API. You download the data once and own it: JSON (and SQLite on the higher tier), WebP images, and full EN/DE/ES translations, with no per-request billing and no dependency on our servers staying up.
A free tier includes 250 exercises with flat-style 512ร512 images, attribution-licensed for commercial in-app use. The Starter tier ($199) adds the full catalog in classic white-background style. Standard ($399) adds transparent 1024px images, looping animations, exercise relations (similar/progressions/regressions), workout templates, and embeddings โ exclusive to that tier.
Every exercise includes muscle-group highlighting, equipment/muscle icons, MET values, and safety/goal tags. Compared to GIF- or JPG-based competitor APIs, RepDB images are transparent WebP with no watermarks, so they drop into any app UI without a white box around them.
Anki
RepDBRepDB's answer:
RepDB is sold as a one-time download, not a metered API โ you own the JSON/SQLite data and WebP images outright, with no rate limits, no per-request billing, and no risk of the vendor cutting off access. It's also the only dataset in this space with EN/DE/ES translations, transparent (alpha-channel) images with no watermark, muscle-group highlighting, safety/goal tags, and looping animations on the higher tier.
RepDB's answer:
RepDB grew out of a consumer workout app its creator was building solo. Sourcing exercise images and data meant either paying for a subscription API with usage caps and no caching rights, or producing everything from scratch. The illustrated, multi-language dataset was built for us first, then split out as its own product once it became clear other indie developers had the same problem and preferred to buy the data outright rather than rent it through an API.
RepDB's answer:
Most alternatives are subscription APIs โ you pay monthly, you're capped on requests, and ExerciseDB's terms of use explicitly forbid caching or storing the data at all, so every image render is a live paid API call. RepDB is the opposite: pay once, download the files, self-host with zero ongoing dependency. It's also the only option offering true DE/ES localization and transparent images instead of a white box behind every exercise.
RepDB's answer:
Solo developers and small teams building fitness or workout-tracking apps (iOS, Android, web) who need licensed exercise images and structured exercise data, but don't want to build their own media pipeline or depend on a rate-limited third-party API.
Based on our record, Anki seems to be more popular. It has been mentiond 850 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Thanks! I'm using [Anki Panky](https://github.com/kamalsacranie/anki-panky) for generating the flashcards and then [Anki](https://apps.ankiweb.net/) itself for learning them. - Source: Hacker News / 4 months ago
Careful using the Anki name, the original author of the app recently registered a trademark. > Anki is a registered trademark of Ankitects Pty Ltd. https://apps.ankiweb.net/. - Source: Hacker News / 11 months ago
AnkiBuddy transforms the way medical students create study materials by using AI to generate high-quality Anki flashcards from PDF documents in minutes - eliminating hours of manual card creation. Built by Dr. David Topf and using Anvil, AnkiBuddy went from initial idea to working prototype in just 2 months, with Anvil enabling rapid iteration and continuous improvement ever since. - Source: dev.to / 12 months ago
To mirror the sibling comment: https://apps.ankiweb.net/ is * Open Source * Cross-platform * $0 except on iOS * Popular enough to have a community and ecosystem around it. - Source: Hacker News / about 1 year ago
Anki (spaced repetition): Use it to create cards from your notes for active recall. - Source: dev.to / over 1 year ago
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