AWS S3 Vector is not available in all AWS regions during its preview release phase. The service is currently limited to a subset of AWS regions, including US East (Northern Virginia), US East (Ohio), and Europe (Frankfurt). This limited regional availability is typical for new AWS services during preview periods, as AWS gradually expands availability based on customer demand, infrastructure readiness, and service stability. The restricted availability may impact global applications that require low-latency access from multiple geographic locations or have data residency requirements in specific regions.
Regional limitations can significantly affect application architecture and performance, especially for globally distributed applications. If your primary user base or data sources are located in regions where S3 Vector isn’t available, you’ll need to account for increased latency when accessing vector search capabilities across regions. Data transfer costs will also apply when moving data between regions, and you’ll need to consider data sovereignty and compliance requirements that might restrict where vector data can be stored and processed.
AWS typically expands regional availability for preview services based on customer feedback and demand patterns. You should monitor AWS announcements and the S3 Vector documentation for updates on regional expansion. In the meantime, you can design your architecture to accommodate the current regional limitations by selecting the nearest available region that meets your latency and compliance requirements. For applications requiring global availability, consider implementing caching strategies, regional data replication patterns, or hybrid architectures that can adapt as S3 Vector becomes available in additional regions. You should also evaluate whether the current regional availability aligns with your other AWS services to minimize cross-region data transfer and optimize overall application performance.
Will Amazon S3 vectors kill vector databases or save them?
S3 vectors looks great particularly in terms of price and integration into the AWS ecosystem. So naturally, there are a lot of hot takes. I’ve seen folks on social media and in engineering circles say this could be the end of purpose-built vector databases—Milvus, Pinecone, Qdrant, and others included. Bold claim, right? As a group of people who’s spent way too many late nights thinking about vector search, we have to admit that: S3 Vectors does bring something interesting to the table, especially around cost and integration within the AWS ecosystem. But instead of “killing” vector databases, I see it fitting into the ecosystem as a complementary piece. In fact, its real future probably lies in working with professional vector databases, not replacing them.
Check out James’ post to learn why we think that—looking at it from three angles: the tech itself, what it can and can’t do, and what it means for the market. We’ll also share S3 vectors’ strenghs and weakness and in what situations you should choose an alternative such as Milvus and Zilliz Cloud.
Will Amazon S3 Vectors Kill Vector Databases—or Save Them?
Or if you’d like to compare Amazon S3 vectors with other specialized vector databases, visit our comparison page for more details: Vector Database Comparison