Anyone shopping for translation software quickly meets two acronyms. CAT, for computer-assisted translation, and TMS, for translation management system. Vendors often use both terms for the same product, and buyers are left wondering whether they need one, the other or both.
The distinction is simpler than it looks. A CAT editor is where linguists do the translating. A TMS is where organisations manage who translates what, when and how. Modern platforms increasingly combine the two, but understanding each role helps you choose wisely.
What the CAT editor does
The editor is the linguist's workspace. It shows the source text split into segments, with a target field next to each. As the translator works, it offers matches from translation memory, highlights approved terms from the termbase, suggests machine translation drafts if enabled, and runs quality checks for numbers, tags, consistency and spelling.
Everything in the editor is designed to help one person, or a small team, translate and review accurately and efficiently. Its value is measured in words per hour, consistency and error rates.
What the TMS does
A translation management system sits above the editor. It receives content from source systems, creates projects, assigns tasks to translators and reviewers, tracks deadlines, manages costs and delivers finished files back to where they belong. It stores memories and termbases centrally so that every project benefits from previous work.
Its value is measured in throughput, turnaround time, visibility and cost control across many projects and languages.
Who needs which
A freelance translator mostly needs a good editor. Project management features help, but a freelancer juggling a handful of clients can manage with simple deadlines and folders.
A language service provider handling hundreds of projects a month needs both. Project managers rely on workflow automation, vendor management and reporting, while linguists need a fast, reliable editor.
A company with in-house localization, such as a software vendor or e-commerce brand, typically needs strong integration features in its TMS so that content flows automatically from code repositories and content management systems.
Game studios are a telling example of this pattern. Their titles ship with hundreds of thousands of strings across dialogue, menus and tutorials, often into a dozen languages at once, which is exactly the kind of volume a TMS is built to orchestrate. In practice, studios split the work: repetitive system text moves through machine translation with post-editing, while story and character dialogue go to dedicated video game localization teams who handle tone, humor and cultural references. If this use case is part of your evaluation, test whether the platform handles string-based formats, screenshots for context and locked segments, not just documents.
Searching for the right fit
When translators and buyers search for a tool CAT users genuinely recommend, they often find products that combine editor and management features in one browser-based platform. This approach has clear advantages: one login, one shared memory, no file exchanges between separate systems, and real-time visibility of progress for everyone involved.
Check, though, that the combined product is strong on both sides. Some platforms excel at workflows but offer a clumsy editor; others have a great editor with limited project tools.
Integration matters most at scale
For organisations, the biggest gains often come from connectors. When the system pulls new content automatically from a website, an app repository or a product information system, and pushes translations back, manual copying disappears. Fewer manual steps mean fewer errors and faster releases.
Ask vendors which connectors exist today, not which ones are planned.
Collaboration features
Translation is collaborative. Translators ask questions, reviewers suggest changes, clients approve terminology. Comment threads attached to segments, query management and role-based permissions keep that communication in context instead of scattered across emails. These features usually sit at the boundary between editor and TMS, and they are worth testing carefully.
Reporting and costs
Management features also include analytics: how many words were translated, how much was reused from memory, how long reviews took, which languages are behind schedule. These numbers help justify budgets, negotiate rates fairly and identify bottlenecks.
Desktop versus cloud
Traditional editors were desktop applications installed on each translator's computer, with project packages sent back and forth. Cloud platforms run in a browser and keep everything on a central server. Desktop software still appeals to some experienced linguists who value offline work and deep customisation. Cloud platforms win on collaboration, onboarding speed and central control of data. Many organisations now prefer cloud for most work while allowing desktop exchange formats for linguists who insist on their own setup.
Security and data ownership
Whichever architecture you choose, clarify who owns the memories and termbases. They represent years of investment and should remain yours if you change provider. Check export formats, data location, encryption and access controls. For regulated industries, ask for documentation that your compliance team can review before signing.
Pricing models
Editors are often priced per user, while management platforms may charge per user, per word volume or per connector. Model your expected usage over a year rather than comparing headline prices, and remember to include freelancers who may need access.
Making the decision
List your real needs first. How many languages, how many projects per month, which file types, which source systems, how many linguists? Then run a pilot with two or three platforms on actual content. Involve both project managers and translators in the evaluation, because a system that pleases one group and frustrates the other will not deliver its promised benefits.
One ecosystem, two jobs
The editor and the management layer serve different people with different goals, but they share the same foundation: translation memories, termbases and quality data. When both are strong and well connected, translators work comfortably, managers see everything, and clients receive consistent translations on time.