Storing And Querying Vectors
aws/agent-toolkit-for-aws/skills/specialized-skills/storage-skills/storing-and-querying-vectorsby awsdf2ab44e485b28358353d827e5ebafbe267cce9fNo license2.8K starsListed Oct 9, 2026Updated Oct 9, 2026Repository updated today
Store and query vector embeddings using Amazon S3 Vectors, a cost-effective long-term vector storage service with its own API namespace (s3vectors). Triggers on: create S3 vector bucket, vector index, store embeddings, semantic search, RAG vector storage, similarity search, vector database, migrate from other vector databases. Do NOT use for: querying tabular data (use querying-data-lake), S3 object storage, or hundreds/thousands of sustained QPS (use OpenSearch).
Only the file list is public. File contents are available once the skill is installed in a workspace.
| Path | Size | Type |
|---|---|---|
| references/limits-and-patterns.md | 2.7 KB | text/markdown |
| references/metadata-filtering.md | 2.1 KB | text/markdown |
| SKILL.md | 7.4 KB | text/markdown |
Source and attribution
Source:aws/agent-toolkit-for-awsinskills/specialized-skills/storage-skills/storing-and-querying-vectorsat commitdf2ab44
License: No license
Content belongs to its original authors. SourceWeft indexes it from a public repository.
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