Milvus is recognized for its robust architecture, scalability, and seamless integration with ML frameworks. let’s explore how Milvus works, its key features, use cases, and why it stands out in the vector database landscape.
FEATURES OF MILVUS
Milvus is a vector database that allows us to store, index, and query large-scale, high-dimensional vectors.
I. Scalability and Performance:
- Horizontal Scaling: Milvus can scale horizontally across multiple nodes. So it can handle vast amounts of data (billions of rows) without compromising performance.
- Dynamic Segment Placement: Milvus optimizes data distribution across nodes dynamically. This ensure efficient resource utilization and reduces query response times.
- GPU Acceleration: Milvus supports GPU acceleration
II. Advanced Vector Indexing:
- Multiple ANN Algorithms: Milvus supports a range of Approximate Nearest Neighbor (ANN) search algorithms, including HNSW (Hierarchical Navigable Small World), IVF_FLAT, and RNSG.
- Hybrid Query Support: Milvus can handle both vector-based and scalar-based queries simultaneously, making it versatile for applications that require both types of searches.
