Turbopuffer vs Elasticsearch
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 Elasticsearch 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
- Elasticsearch offers more deployment options
- Turbopuffer is more cost-effective
- Elasticsearch has more permissive licensing
- Elasticsearch has 5 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.
Elasticsearch
Elasticsearch is one of Europe's most widely deployed open-source search engines that includes native vector database capabilities. It combines dense vector search with traditional full-text BM25 keyword search for powerful hybrid retrieval, making it ideal for RAG applications that need both semantic and lexical search capabilities.
Feature Comparison
Infrastructure & Technical Details
| Feature | Turbopuffer | Elasticsearch |
|---|---|---|
| Deployment | BYOC, Managed Cloud | Self-Hosted, Managed Cloud, Serverless |
| Cost | Minimum commitment $64/month | Serverless: usage-based (ECU); Hosted: starts ~$95/month; Self-hosted: free (infra cost only) |
| License | Proprietary | AGPL v3 / SSPL / Elastic License 2.0 |
| Index Types | SPFresh | HNSW, int8_hnsw, int4_hnsw, bbq_hnsw, Flat |
| Cloud Providers | AWS, GCP, Azure | AWS, Azure, GCP, Alibaba Cloud |
| Regional Flexibility | high | high |
| Strengths | 7 | 12 |
| Weaknesses | 7 | 8 |