Crowdin vs Localazy: What are the differences?

Introduction:

In this comparison, we will explore the key differences between Crowdin and Localazy.

1. Pricing Model: Crowdin offers a subscription-based pricing model, where the cost is determined by the size of the project and the number of contributors. On the other hand, Localazy follows a pay-as-you-go pricing model, where users only pay for the actual translations used in their apps or projects.

2. Translation Memory: Crowdin provides a Translation Memory feature, which allows users to reuse previously translated segments to save time and improve consistency. Localazy does not offer a built-in Translation Memory feature, requiring users to manually keep track of and reuse translations.

3. Integration and Compatibility: Crowdin offers integrations with a wide range of third-party tools and platforms, including GitHub, Bitbucket, Jira, and many more. Localazy, however, focuses primarily on Android and iOS apps, providing libraries and plugins specifically designed for these platforms.

4. Community Collaboration: Crowdin emphasizes community collaboration and offers various features to crowdsource translations by engaging volunteers and contributors. Localazy, on the other hand, focuses more on professional translation services, providing high-quality translations through its network of language partners.

5. Workflow and Project Management: Crowdin provides a comprehensive project management interface with features like task assignment, progress tracking, and notifications. Localazy, while offering basic project management capabilities, is more streamlined and focuses primarily on the translation process itself.

6. Automation and Machine Translation: Crowdin offers automation options, such as pseudo-localization, machine translation, and auto spell-check. Localazy, however, does not provide similar built-in automation features and instead focuses on manual translation with improved quality control.

In summary, Crowdin and Localazy differ in their pricing models, translation memory capabilities, integration compatibility, emphasis on community collaboration, project management features, and availability of automation options.