Turbopuffer vs MongoDB Atlas Vector Search
Compare deployment options, cost efficiency, and features to choose the right vector database for your application.
Database Comparison
Turbopuffer takes the lead.
Both Turbopuffer and MongoDB Atlas Vector Search are powerful vector databases designed for efficient similarity search and storage. However, their deployment options and features differ in important ways.
Why Turbopuffer:
- Turbopuffer ranks higher overall
- MongoDB Atlas Vector Search offers more deployment options
- Turbopuffer is more cost-effective
- MongoDB Atlas Vector Search has more permissive licensing
- MongoDB Atlas Vector Search has 6 more strengths
Turbopuffer
⭐Turbopuffer is a fully managed cloud vector database built around a centroid-optimized SPFresh index. It is designed for extremely low-cost, large-scale storage, leveraging object storage engines like S3, GCS, or Azure Blob.
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.
Feature Comparison
Infrastructure & Technical Details
| Feature | Turbopuffer | MongoDB Atlas Vector Search |
|---|---|---|
| Deployment | BYOC, Managed Cloud | Managed Cloud, Self-Hosted (Enterprise), Community Edition |
| Cost | Minimum commitment $64/month | Free tier: M0 (512MB); Flex: $8-$30/mo; Dedicated: starts $57/mo (M10); Community: Free |
| License | Proprietary | SSPL (self-managed) / Proprietary (Atlas Cloud) |
| Index Types | SPFresh | Hierarchical Navigable Small World (HNSW-like), Quantized indexes |
| Cloud Providers | AWS, GCP, Azure | AWS, Azure, GCP |
| Regional Flexibility | high | high |
| Strengths | 7 | 13 |
| Weaknesses | 7 | 10 |