Weaviate 推出 blobHash 属性类型,解决多模态搜索中同一图片、音视频在对象存储和向量数据库各存一份的问题。媒体仍按原方式传入,向量化完成后 Weaviate 只保留 SHA-256 哈希而非完整文件,向量与可搜索表示留在 Weaviate,原始资产留在对象存储。更新时通过比对哈希判断内容是否变化,仅在真正改动时重新向量化,减少磁盘占用和重复嵌入。
Why are you storing your images twice?
If you're building multimodal search, you've probably seen this: your images, audio, or video live in S3, that's your source of truth.
But to vectorize them, you send the raw bytes into your vector database... and then they just sit there. Same file, two places, two bills.
You can easily fix this with the 𝗯𝗹𝗼𝗯𝗛𝗮𝘀𝗵 property type.
You send the media in exactly the same way you always have, the vectorizer embeds the real content, and once that's done, Weaviate keeps a SHA-256 hash instead of the full payload. The vector and the searchable representation stay with Weaviate. The actual asset stays in object storage where it belongs.
- No duplicated media sitting in your database eating disk
- A clean split between your vector layer and your system of record
- Weaviate compares hashes on update, so you only re-vectorize when the content actually changed
No more guessing whether that image was modified, no more re-embedding thousands of files "just in case."
Learn more in the blog: https://weaviate.io/blog/weaviate-1-37-release#blobhash-property-type?utm_source=channels&utm_medium=w_social&utm_campaign=1.37_release&utm_content=800980983
来源:Weaviate AI Database · x.com