How does Parse measure this comparison?

Name: Qdrant vs Redis AI comparison
Creator: Parse

Parse reads answers from AI assistants and records every claim that compares the two brands, then groups those claims by the need they speak to. This page is based on 13 claims collected between Mar 22, 2026 and Jul 24, 2026. It is a reading of what AI says, not a review by Parse.

Brands
Qdrant
vs Redis

Qdrantvs Redis

Qdrant vs Redis, according to AI

Which one AI picks, and when.

Data as of Jul 24, 2026 · Based on 13 AI claims comparing the two · See how Parse measures this

Head to head

The two are furthest apart on strength, where Qdrant leads by 17 points.

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What AI Says About Qdrant vs Redis | Parse

Brands
Qdrant
vs Redis

Qdrantvs Redis

Qdrant vs Redis, according to AI

Which one AI picks, and when.

Data as of Jul 24, 2026 · Based on 13 AI claims comparing the two · See how Parse measures this

Head to head

The two are furthest apart on strength, where Qdrant leads by 17 points.

Qdrant and Redis compared on the Parse Score and its three pillars
Measure	Qdrant	Redis
Parse Score	88

Qdrant and Redis compared on the Parse Score and its three pillars
Measure	Qdrant	Redis
Parse Score	88

Strength (widest gap)	69	52

Reach	76	75

Authority	71	75

What AI says about Qdrant

Developer Backend & Vector Search Services · #1

What AI says about Redis

LLM Security and Governance Platforms · #5

Compare your brand against Qdrant or Redis. Free check, no account.

What buyers actually ask

The problem is, our vector search is slow under high load. What's the best vector database designed for high-throughput, low-latency production use?
My goal is to cache LLM responses to reduce latency and cost. What's the best semantic caching solution?
I am looking for a database that supports vector search natively and does not require a separate bolt-on index.

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Questions

How does Parse measure this comparison?: Parse reads answers from AI assistants and records every claim that compares the two brands, then groups those claims by the need they speak to. This page is based on 13 claims collected between Mar 22, 2026 and Jul 24, 2026. It is a reading of what AI says, not a review by Parse.

Track this comparison

Weekly insights tell you how often AI recommends each brand, and which prompts and sources explain the result.

Track this comparison

The problem is, our vector search is slow under high load. What's the best vector database designed for high-throughput, low-latency production use?
My goal is to cache LLM responses to reduce latency and cost. What's the best semantic caching solution?
I am looking for a database that supports vector search natively and does not require a separate bolt-on index.

QdrantvsWeaviate
MilvusvsQdrant
PineconevsQdrant
pgvectorvsQdrant
Amazon ElastiCachevsRedis
PostgreSQLvsQdrant

How does Parse measure this comparison?: Parse reads answers from AI assistants and records every claim that compares the two brands, then groups those claims by the need they speak to. This page is based on 13 claims collected between Mar 22, 2026 and Jul 24, 2026. It is a reading of what AI says, not a review by Parse.