Amazon S3 Vectors vs Qdrant
Which one do AI engines recommend, and how do they differ on price, fit and features?
The short answer
Qdrant is the stronger AI pick in Vector Databases: it has a visibility score of 60.5 versus 1.2 for Amazon S3 Vectors, and ranks ahead in 100% of the answers that name both.
Choose Amazon S3 Vectors if…
- very low storage cost for infrequently queried data
Choose Qdrant if…
- You want the brand AI engines rank higher (60.5 vs 1.2)
- You need a self-hosted or on-premises option
- You need SOC 2 Type 2 or HIPAA coverage
- High performance and memory efficiency, written in Rust
AI visibility side by side
Latest weekly run · Nov 2
| Metric | Amazon S3 Vectors | Qdrant |
|---|---|---|
| Visibility score | 1.2% | 60.5% |
| Change vs last week | New | New |
| Rank in Vector Databases | #24 | #2 |
| Share of voice | 0.5% | 13.4% |
| Mentions this run | 2 | 63 |
| Positive in AI answers | — | 68% |
The stronger value in each row is marked with a ✓.
Visibility score trend
Weekly runs over the last 60 days
Amazon S3 Vectors 0pp · Qdrant 0pp over 0 weekly runs.
Engine by engine
Qdrant leads on 3 of 3 engines
Head to head in AI answers
2 engine answers name both brands
| Prompt | Engine | Amazon S3 Vectors | Qdrant |
|---|---|---|---|
| What are the best Vector Databases tools in 2026? | Perplexity | #10 | #1 |
| Most affordable vector database that is still reliable | Perplexity | #3 | #2 |
Features, pricing & fit
| Dimension | Amazon S3 Vectors | Qdrant |
|---|---|---|
| Pricing model | — | Usage-based |
| Entry price | — | Contact sales |
| Free plan | — | Yes |
| Deployment | Fully managed and serverless, with no dedicated clusters to run | Managed cloud, hybrid cloud, private cloud (air-gapped), self-hosted on-premises, and edge |
| Compliance | — | SOC 2 Type 2, HIPAA |
| Support | — | Community support via Discord on the free tier, Standard tier: email and ticket portal, 10x5 business hours, Premium tier: 24/7 support with private Slack, Discord or Teams channels, Enterprise tier: custom response SLA and advisory services |
| Founded | 2025 | 2021 |
| Headquarters | — | Berlin, Germany |
| Employees | — | 51–200 |
| Funding | — | Series B · $88M raised |
| Best for | — | Developers and teams building RAG, semantic search and recommendation systems that need hybrid search and metadata filtering, either self-hosted or managed |
Plans side by side
Amazon S3 Vectors
Pricing not available.
Qdrant
Pros and cons
Themes from the AI answers that mention each brand
Amazon S3 Vectors
- very low storage cost for infrequently queried data
- higher latency
- fewer database-like capabilities
Qdrant
- High performance and memory efficiency, written in Rust
- Strong metadata and complex payload filtering
- Free tier for prototyping and testing
- Open-source option with flexible self-hosting
- Strong default choice for startups and production RAG
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
Cite as: SlateIndex, “Amazon S3 Vectors vs Qdrant”, https://slateindex.ai/compare/amazon-s3-vectors-vs-qdrant, data of Nov 2, 2026. Licence: CC BY 4.0.