Image Similarity Search
Powering your image similarity search system with Zilliz Cloud (the fully managed version of Milvus)
Image Similarity Search with Zilliz Cloud Vector Database
Discover visually similar images effortlessly with Zilliz Cloud-powered image similarity search engines, proving valuable in various fields like e-commerce and art.
Effortlessly Accommodate Your Spiking Image 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. Manage billions of image vectors within hours with efficient bulk inserts.
High-Performant Image Similarity 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.
Real-Time Image Search Results 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 image search systems, guaranteeing uninterrupted service reliability even in unexpected events through multiple replicas, component isolation, and robust backup and sync capabilities.
Start with Simplicity and Amplified Productivity
Deploy a large-scale image similarity search service in minutes with user-friendly SDKs in multiple languages and streamlined data operations, ensuring an intuitive user experience.
How Zilliz Cloud Powers Image Similarity Search
A Zilliz-powered image similarity search system works in the following ways:
- Images are transformed into vector embeddings using an embedding model.
- Image embeddings are ingested and stored in Zilliz Cloud.
- Users search for images similar to their query images.
- The image query is transformed into vector embeddings using an embedding model.
- The query embeddings are sent to Zilliz Cloud for a similarity search.
- Zilliz Cloud performs approximate nearest neighbor (ANN) searches and retrieves the Top-K most relevant results by comparing the spatial distance between the query and image vectors.
- Zilliz Cloud returns the Top-K results to the user.
Success Stories
Industry leaders worldwide use Milvus or Zilliz Cloud (the fully managed Milvus) to build their image search systems.
90% reduction
in search latency
Sharp reduction
on $ and time
Easily scale
as business grows
Handled tens of millions of
vector embeddings with fast scaling capability
Achieved millisecond-level
query speed with optimal user experience
Reshaped the future of fashion
with a harmonious fusion of human creativity and machine intelligence
90% reduction
in search latency
Sharp reduction
on $ and time
Easily scale
as business grows
Handled tens of millions of
vector embeddings with fast scaling capability
Achieved millisecond-level
query speed with optimal user experience
Reshaped the future of fashion
with a harmonious fusion of human creativity and machine intelligence