Elasticsearch vs Redis Vector Search
Compare deployment options, cost efficiency, and features to choose the right vector database for your application.
Database Comparison
Elasticsearch takes the lead.
Both Elasticsearch and Redis Vector Search are powerful vector databases designed for efficient similarity search and storage. However, their deployment options and features differ in important ways.
Why Elasticsearch:
- Elasticsearch ranks higher overall
- Elasticsearch has 1 more strengths
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.
Redis Vector Search
Redis provides vector similarity search through Redis Stack (RediSearch module), enabling low-latency semantic search and RAG applications. As an in-memory database, Redis excels at small-to-medium scale vector workloads requiring ultra-low latency. It integrates vector search with Redis's core data structures, making it ideal for real-time AI applications, semantic caching, and RAG systems.
Feature Comparison
Infrastructure & Technical Details
| Feature | Elasticsearch | Redis Vector Search |
|---|---|---|
| Deployment | Self-Hosted, Managed Cloud, Serverless | Self-Hosted (Redis Stack), Redis Enterprise, Redis Cloud |
| Cost | Serverless: usage-based (ECU); Hosted: starts ~$95/month; Self-hosted: free (infra cost only) | Redis Stack: Free (self-host); Cloud: starts $5/mo; Enterprise: shard-based pricing; Redis Flex: hybrid RAM+SSD |
| License | AGPL v3 / SSPL / Elastic License 2.0 | RSALv2 / SSPLv1 / AGPLv3 |
| Index Types | HNSW, int8_hnsw, int4_hnsw, bbq_hnsw, Flat | FLAT, HNSW |
| Cloud Providers | AWS, Azure, GCP, Alibaba Cloud | AWS, Azure, GCP |
| Regional Flexibility | high | high |
| Strengths | 12 | 11 |
| Weaknesses | 8 | 12 |