Video Similarity Search With Zilliz Cloud Vector Database
Discover videos resembling your video query with Zilliz Cloud-powered video search engines, proven beneficial for video surveillance, deduplication, recommendation, and beyond.
High-Performant Video Search with Unparalleled Precision
Experience a 10x performance boost on Zilliz Cloud with advanced indexing algorithms, ensuring millisecond-level latency. Benefit from unparalleled precision using hybrid vector search with scalar filtering and range search capability.
Efficiently Managing Your Spiking Video Search Data
Say goodbye to data size concerns with Zilliz Cloud. Experience horizontal and independent scaling for computing and storage, aligning with your budget and evolving needs.
Real-Time Responses for Optimized User Experience
Zilliz Cloud guarantees consistently up-to-date search results through real-time data insertion, deletion, and seamless data flows, significantly optimizing the user experience.
Always On, Always Reliable
Zilliz Cloud builds resilient video search systems, guaranteeing uninterrupted service reliability, even in unexpected events through multiple replicas, component isolation, and robust backup and sync capabilities.
Simple Start, Amplified Productivity
Deploy a large-scale similarity search service in minutes with user-friendly SDKs in multiple languages and streamlined data operations, ensuring an intuitive user experience.
Zilliz Cloudが動画類似性検索を強化する方法
Zillizを利用した動画類似検索システムは、以下のような仕組みになっている：
- 動画は埋め込みモデルを用いてベクトル埋め込みに変換される。
- 動画埋め込みはZilliz Cloudに取り込まれ、保存される。
- ユーザは、自分の動画に似た動画を検索する。
- 動画のクエリは、埋め込みモデルを使用してベクトル埋め込みに変換されます。
- クエリ埋め込みは類似検索のためにZilliz Cloudに送られる。
- Zilliz CloudはANN検索を実行し、最も関連性の高いトップKの結果を取得します。
- Zilliz CloudはTop-Kの結果をユーザに返します。
成功事例
世界中の業界リーダーがMilvusまたはZilliz Cloud（フルマネージドMilvus）を使用して動画検索ビジネスを展開しています。
> 100M
embedding vector storage and searching
Seamlessly integration
with various internal systems and tech stacks
Enhanced real-time data retrieval
with reduced latency and increased system availability
How Milvus Transformed BIGO's Video Deduplication System for Optimal Throughput and User Experience
今すぐ読む<200ms
search response time with a high recall rate
>700 million
embedding vectors indexing and management
Significantly increased
query throughput without compromising performance
> 100M
embedding vector storage and searching
Seamlessly integration
with various internal systems and tech stacks
Enhanced real-time data retrieval
with reduced latency and increased system availability
How Milvus Transformed BIGO's Video Deduplication System for Optimal Throughput and User Experience
今すぐ読む<200ms
search response time with a high recall rate
>700 million
embedding vectors indexing and management
Significantly increased
query throughput without compromising performance