MongoDB Atlas Vector Search vs Milvus
Compare deployment options, cost efficiency, and features to choose the right vector database for your application.
Database Comparison
Two competitive vector databases, closely matched.
Both MongoDB Atlas Vector Search and Milvus are powerful vector databases designed for efficient similarity search and storage. They show comparable performance across key metrics.
Key similarities:
- MongoDB Atlas Vector Search offers more deployment options
- Milvus is more cost-effective
- Milvus has more permissive licensing
- MongoDB Atlas Vector Search has 4 more strengths
MongoDB Atlas Vector Search
MongoDB Atlas Vector Search is a native vector database capability built directly into MongoDB Atlas, eliminating data synchronization between operational and vector databases. It enables hybrid queries combining vector similarity with MongoDB's powerful document model, metadata filtering, aggregation pipelines, and geospatial search—all within a single unified platform.
Milvus
Milvus is a flexible, open-source vector database built for local and hybrid cloud deployment. With support for IVF, HNSW, and DiskANN, it provides the widest indexing variety for tuning performance on large-scale workloads. Milvus is ideal when you want control, configurability, and low infrastructure cost.
Feature Comparison
Infrastructure & Technical Details
| Feature | MongoDB Atlas Vector Search | Milvus |
|---|---|---|
| Deployment | Managed Cloud, Self-Hosted (Enterprise), Community Edition | Self-Hosted, Managed Cloud |
| Cost | Free tier: M0 (512MB); Flex: $8-$30/mo; Dedicated: starts $57/mo (M10); Community: Free | Free (self-hosted), infra cost only |
| License | SSPL (self-managed) / Proprietary (Atlas Cloud) | Apache 2.0 |
| Index Types | Hierarchical Navigable Small World (HNSW-like), Quantized indexes | IVF, HNSW, DiskANN |
| Cloud Providers | AWS, Azure, GCP | Any |
| Regional Flexibility | high | high |
| Strengths | 13 | 9 |
| Weaknesses | 10 | 6 |