Hey everyone,
As a side project, I wanted to build an alternative to legacy fragrance databases that are notoriously plagued by 10+ ad networks, sluggish client-side rendering, and bloated tracking scripts.
The project is Olfactionary.
The Engineering & Data Challenge:
Relational Scale: Built a structured relational schema linking 12,000+ fragrances, 980+ houses, and 230+ perfumers to 3,600+ individual aroma chemicals/botanicals across 17 olfactory families.
Data Integrity: Rather than scraping raw marketing copy, entries are triangulated against patent filings, academic research, PubChem records, and IFRA standards with verification tags.
Performance Focus: Prioritized instant client-side search indexing and lightweight page weights to ensure sub-second loads without algorithmic feeds.
Open Literature: Digitized and indexed out-of-copyright historical perfumery texts dating back to antiquity.
Would love feedback on search latency, UI responsiveness, and suggestions on how you'd handle deep relational filtering at this scale.
Live link: https://olfactionary.com
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