Developer builds Mandarin learning platform with 100k+ TV clips using Rust and Next.js

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A developer has launched MandarinClips, a language learning platform that indexes over 100,000 dialogue segments from Chinese movies and TV series to support immersive learning. The platform is built with a Rust backend using the Axum framework and a Next.js 15 frontend, running on a single two-core VPS. To handle fast search across a large dataset, the project uses PostgreSQL with the pg_trgm trigram extension and GIN indexing, enabling fuzzy text searches in under one millisecond. Media storage is handled via Backblaze B2 proxied through Cloudflare CDN, eliminating egress costs. The project was shared on DEV Community as a technical deep dive into the architecture and engineering decisions behind the platform.

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