ormDB for E-Commerce
ormDB eliminates N+1 queries on e-commerce product pages through graph fetches that load products with variants, reviews, and related items in a single round-trip. Built-in BM25 full-text search replaces the need for Elasticsearch, and change streams provide real-time inventory updates.
E-commerce data is deeply relational
A single product page might need: the product, its variants (size, color), images, reviews with authors, related products, inventory levels, and pricing rules. With PostgreSQL and an ORM, that’s 7+ separate queries — the classic N+1 problem.
ormDB for product catalogs
ormDB is a relational database engine that loads entire product graphs in one round-trip. Define your product entity with relations to variants, images, and reviews. A single graph fetch returns the complete product page data as structured entity blocks.
Full-text search is built in. BM25-ranked search with phrase matching means you don’t need Elasticsearch for product search. Your product catalog and search index live in one database.
Change streams push real-time inventory updates. When stock levels change, ormDB emits events that your storefront can subscribe to — no polling, no stale inventory displays.
ACID transactions ensure order processing integrity. Payment, inventory deduction, and order creation happen atomically.
Frequently Asked Questions
Can ormDB replace Elasticsearch for product search?
For most e-commerce search needs, yes. ormDB includes BM25-ranked full-text search with phrase matching and boolean queries built in. You don't need a separate search infrastructure for product catalog search.
How does ormDB handle product pages with many relations?
A product page with variants, images, reviews, and related products loads in one graph fetch. ormDB returns the entire product graph in a single round-trip.