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What are the limitations or quotas for using AWS S3 Vector?

AWS S3 Vector has several important limitations and quotas that developers need to consider when designing their applications. Each vector bucket can contain up to 10,000 vector indexes, and each vector index can store tens of millions of vectors, though AWS hasn’t published exact limits for individual vector counts per index. Vector dimensions are constrained between 1 and 4,096, which accommodates most common embedding models but may limit use cases requiring higher-dimensional representations. The service currently supports only floating-point (float32) vector data, excluding binary embeddings that some applications use for storage efficiency.

Metadata limitations include a maximum of 10 non-filterable metadata keys per vector index, with these keys being unchangeable after index creation. Each vector can have associated metadata, but there are size limits on both the total metadata per vector and the filterable metadata size, though specific byte limits aren’t detailed in the documentation. Regional availability is currently limited during the preview phase, with S3 Vector available only in select regions including Northern Virginia (us-east-1), Ohio (us-east-2), and Frankfurt (eu-central-1) in Europe. This geographic limitation may affect global applications requiring low-latency access from multiple regions.

Operational limitations include the immutability of key vector index parameters after creation. Once you set the dimension size, distance metric, and non-filterable metadata keys for an index, these cannot be modified, requiring careful planning or index recreation for changes. Vector bucket encryption settings are also permanent after creation. Performance characteristics are optimized for infrequent queries rather than high-throughput scenarios, making S3 Vector less suitable for applications requiring thousands of queries per second or ultra-low latency responses. The service is designed for sub-second query performance, which may not meet requirements for real-time applications needing millisecond response times.

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