A translation management system (TMS) is a solution for managing translation projects, large and small, and can integrate glossaries, translation software, and translation memories. There are a number of options on the market, and each solution has its own features and integrations. Some translation management systems include a CAT (computer-assisted translation) component, others don’t and function as a BMS (business management system). To help navigate research for choosing the best option for an organization, Nimdzi offers interactive tools including the TMS Integration Map, TMS Feature Explorer, and the TMS Feature Comparison Tool.
The TMS Feature Explorer is Nimdzi’s handy, interactive tool that uses the latest data on translation management systems and allows users to filter tools by features. If you’re looking to explore features and functionalities across today’s solutions, this is a great place to start.
Before TMS came about, computer-assisted or computer-aided translation (CAT) tools were the main means of properly handling translation tasks. CAT tools allow users to work with bilingual text, that is, the source (original) and the target (translation). The core components of CAT tools usually included a translation memory (TM), a bilingual editing environment (such as an interactive bilingual table), a termbase (TB), and a quality assurance (QA) module.
Over time, these features were no longer enough to effectively deal with the growing and dynamic translation and localization needs of modern enterprises. That’s why a variety of business management features ended up appearing in this type of solution, resulting in the birth of what is now called TMS.
The main difference between a TMS and a BMS is that in a TMS you both translate and manage jobs while in a BMS you just manage jobs/translation tasks. There’s no translation environment per se in the BMS. However, a BMS can connect to different TMS.
Roman is Nimdzi’s VP of Consulting and has over 20 years of experience in localization and continuous improvement work, ranging from solution development, technology change, business process and design to strategic change. He gives practical guidance on the optimization and change of localization process, mindset, technology, and data frameworks. He supports and challenges teams to adopt a purpose-driven lifestyle that leads to radical improvement.
Yulia graduated as a software engineer. Since 2010 she has worked in localization combining strategic, operational, and marketing functions. Her main areas of research are language technology and game localization. Projects Yulia worked on include the Nimdzi Language Technology Atlas, the “Introduction to Language Technology” e-learning course, Nimdzi’s terminology management systems feature explorer, and numerous studies on language technology for enterprise and government clients.