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Vector Databases Are Officially Dead Heres What Aws Just Did Front Page

Are Vector Databases Dead
Are Vector Databases Dead

Are Vector Databases Dead Time is ticking for vector database companies. cloud giant aws has launched the preview of amazon s3 vectors, a new vector storage solution that allows businesses to store and query ai ready data at scale, with cost savings of up to 90% compared to traditional methods. Amazon just dropped a game changer for ai developers: native vector search inside s3. no more managing separate vector databases — just store, index, and query embeddings directly in your.

Databases On Aws
Databases On Aws

Databases On Aws On july 15th, aws quietly ignited a transformation: the launch of amazon s3 vectors, the first ever cloud storage natively designed for vectors. in one bold stroke, the complex infrastructure. By storing infrequently accessed vectors in s3, aws can reduce compute costs for vector databases and save customers money. The whole point of vector search is to circumvent this process by efficiently picking the information your app needs to generate the best response. a vector database keeps the compute load low and the query response fast. Here’s what the data actually reveals about aws s3 vectors versus traditional vector databases, including real cost calculations, performance benchmarks, and the critical factors every enterprise team needs to evaluate before making the switch.

Databases On Aws
Databases On Aws

Databases On Aws The whole point of vector search is to circumvent this process by efficiently picking the information your app needs to generate the best response. a vector database keeps the compute load low and the query response fast. Here’s what the data actually reveals about aws s3 vectors versus traditional vector databases, including real cost calculations, performance benchmarks, and the critical factors every enterprise team needs to evaluate before making the switch. Amazon s3 vectors delivers purpose built, cost optimized vector storage for ai agents, ai inference, and semantic search of your content stored in amazon s3. The emergence of s3 vectors may force existing vector database vendors (like pinecone) to rethink their market positioning and pricing strategies. technical teams now need to reassess existing ai technology stacks to determine which workloads can migrate to s3 vectors for cost optimization. But the new gold rush is happening in unstructured data — and that’s where vector databases are quietly taking over. especially as companies move from “search” to “understanding,” and from static dashboards to intelligent assistants powered by embeddings.

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