Will Amazon S3 Vectors Kill Vector Databases–Or Save Them?
2 days ago
- #Vector Databases
- #AI Infrastructure
- #AWS
- AWS introduced S3 Vectors, a vector storage solution integrated with Amazon S3, sparking debates on its impact on dedicated vector databases.
- Vector search is expensive, sometimes costing more than LLM API calls, highlighting the need for cost-effective solutions.
- Vector databases evolved from memory-only to disk-based and now to object storage like S3 to address cost and scalability.
- S3 Vectors offers ultra-low-cost storage but has limitations in performance, precision, and functionality compared to dedicated vector databases.
- The future of vector storage is tiered, with hot, warm, and cold layers balancing cost, latency, and scale.
- Milvus is advancing with features like hybrid search, multi-tenant isolation, and upcoming AI-native capabilities in version 3.0.
- S3 Vectors validates the demand for vector storage, educates the market, and drives innovation in the industry.