What is SvectorDB?

SvectorDB is a serverless vector database designed for Amazon Web Services, offering instant upserts and deletions without eventual consistency delays. It supports hybrid search by combining vector similarity with Lucene‑style key/value filters and integrates natively with CloudFormation for seamless infrastructure management.

The service exposes an OpenAPI specification, allowing developers to use any language and client library. Built‑in vectorizers for text and images enable rapid embedding creation, while the option to import custom embeddings gives full control over representation quality.

SvectorDB pricing Freemium

Queries $5/million

Writes $20/million

Storage $0.25/gb/mo

Verify on the official pricing page.

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SvectorDB's key features

Serverless vector database for AWS
Hybrid search with Lucene queries
Built-in vectorizers for text images
Instant updates and upserts
Pay-per-request pricing
CloudFormation integration support
OpenAPI spec multi-language clients

SvectorDB use cases

Create a real-time semantic search layer for an enterprise knowledge base, instantly upserting new policy documents, filtering by department, and leveraging hybrid vector‑Lucene queries to surface the most relevant information.
Build a serverless image similarity engine for an e-commerce catalog, automatically generating image embeddings, supporting instant upserts for new product photos, and providing hybrid vector‑Lucene searches to match user‑uploaded images with millions of listings.
Integrate custom domain embeddings into SvectorDB for a medical research portal, allowing clinicians to perform hybrid semantic and keyword searches across thousands of studies while applying filters for study type and publication date, all without managing infrastructure.