Elasticsearch vs Redis Vector Search
Compare deployment options, cost efficiency, and features to choose the right vector database for your application. If you want to compare these models on your data, try Agentset.
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
Vector Databases Are Just One Piece of RAG
Agentset gives you a managed RAG pipeline with the top-ranked models and best practices baked in. No infrastructure to maintain, no vector database to operate.
Trusted by teams building production RAG applications
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.
Build RAG in Minutes, Not Months
Agentset gives you a complete RAG API with fully managed vector storage and retrieval. Upload your data, call the API, and get accurate results from day one.
import { Agentset } from "agentset";
const agentset = new Agentset();
const ns = agentset.namespace("ns_1234");
const results = await ns.search(
"What is multi-head attention?"
);
for (const result of results) {
console.log(result.text);
}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 |