Real Estate Listings Backend With Cached Search and Media Uploads

Added Jun 2025 3 design docs

Every property marketplace stands on its backend: if search is slow, images fail, or data models tangle, no frontend can save the product. This project focuses entirely on building that foundation well for a real estate platform, treating the API itself as the deliverable. The intern designs a relational MySQL schema modeling properties, agents, and clients with the relationships and constraints the domain demands, then implements a full CRUD API in Express and Node.js with validation on every input. Property images are uploaded and served through Multer with proper handling of file types and limits, and JWT authentication secures the API's protected operations. Because search is the most-hit path in any listings product, the intern integrates Redis to cache frequent search results, measuring and demonstrating the latency difference caching makes under repeated queries. Working backend-only sharpens skills that fullstack projects often blur past: careful schema design, query optimization with joins and indexes, cache invalidation strategy, and API contracts robust enough for any client to build on. The intern finishes with a documented, production-shaped service that proves they can own the data layer of a marketplace.

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