ElasticsearchThe search database for AI
vs
QdrantOpen-Source Vector Search Engine written in Rust
Comparison · Vector Databases · weekly run Nov 2
Elasticsearch 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 14.3 for Elasticsearch, and ranks ahead in 94% of the answers that name both.
Choose Elasticsearch if…
- You need SOC 2 Type II or ISO/IEC 27001 or ISO/IEC 27017 or ISO/IEC 27018 or ISO/IEC 27701 or FedRAMP Moderate or FedRAMP High or PCI DSS or CSA STAR coverage
- You prefer a larger, established vendor (1,001–5,000 employees)
- Strongest general enterprise choice for vector search alongside full-text search, logs, and analytics
- Widely deployed, often cited as the most widely deployed vector-capable search engine
Choose Qdrant if…
- You want the brand AI engines rank higher (60.5 vs 14.3)
- AI answers describe it more positively (68% vs 30% positive)
- You need a self-hosted or on-premises option
- You need SOC 2 Type 2 coverage
AI visibility side by side
Latest weekly run · Nov 2
| Metric | Elasticsearch | Qdrant |
|---|---|---|
| Visibility score | 14.3% | 60.5% |
| Change vs last week | New | New |
| Rank in Vector Databases | #7 | #2 |
| Share of voice | 5.1% | 13.4% |
| Mentions this run | 24 | 63 |
| Positive in AI answers | 30% | 68% |
The stronger value in each row is marked with a ✓.
Visibility score trend
Weekly runs over the last 60 days
Elasticsearch 0pp · Qdrant 0pp over 0 weekly runs.
Engine by engine
Qdrant leads on 3 of 3 engines
ChatGPT
AI Mode
Perplexity
ElasticsearchQdrant
Head to head in AI answers
18 engine answers name both brands
1Elasticsearch ranked higher
17Qdrant ranked higher
| Prompt | Engine | Elasticsearch | Qdrant |
|---|---|---|---|
| How do I choose a vector database for a mid-market team? | ChatGPT | #7 | #3 |
| How do companies store and search embeddings without a dedicated tool? | AI Mode | #4 | #2 |
| What are the best Vector Databases tools in 2026? | ChatGPT | #8 | #2 |
| What are the best Vector Databases tools in 2026? | AI Mode | #7 | #3 |
| What are the best Vector Databases tools in 2026? | Perplexity | #7 | #1 |
| Top vector database options for B2B SaaS companies | Perplexity | #6 | #1 |
| Best vector database for enterprise | Perplexity | #1 | #5 |
| Compare the leading Vector Databases platforms | ChatGPT | #7 | #2 |
| Compare the leading Vector Databases platforms | Perplexity | #6 | #3 |
| Which vector database has the best reviews? | AI Mode | #5 | #3 |
| Alternatives to the most popular vector database | ChatGPT | #8 | #2 |
| Alternatives to the most popular vector database | Perplexity | #7 | #2 |
Features, pricing & fit
| Dimension | Elasticsearch | Qdrant |
|---|---|---|
| Pricing model | — | Usage-based |
| Entry price | — | Contact sales |
| Free plan | — | Yes |
| Deployment | Elastic Cloud Serverless, Elastic Cloud Hosted, or self-managed on premises, in private, hybrid or air-gapped environments. | Managed cloud, hybrid cloud, private cloud (air-gapped), self-hosted on-premises, and edge |
| Compliance | SOC 2 Type II, ISO/IEC 27001, ISO/IEC 27017, ISO/IEC 27018, ISO/IEC 27701, FedRAMP Moderate, FedRAMP High, PCI DSS, HIPAA, CSA STAR | SOC 2 Type 2, HIPAA |
| Support | Four support tiers depending on Elastic Cloud subscription tier, 99.95% monthly uptime SLA for Platinum and Enterprise tiers | 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 | 2012 | 2021 |
| Headquarters | San Francisco, California | Berlin, Germany |
| Employees | 1,001–5,000 | 51–200 |
| Funding | IPO (NYSE) | Series B · $88M raised |
| Best for | Teams building AI search, RAG and vector applications, and organizations that want search, observability and security on one data platform. | 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
Elasticsearch
Pricing not available.
Qdrant
Free Tier$0forever
Standard TierCustomusage-based
Premium TierCustomminimum spend required
Pros and cons
Themes from the AI answers that mention each brand
Elasticsearch
- Strongest general enterprise choice for vector search alongside full-text search, logs, and analytics
- Widely deployed, often cited as the most widely deployed vector-capable search engine
- Hybrid keyword-plus-semantic search via dense vectors and inverted indexes
- Suited to consolidated stacks and broader search, logging, analytics, or observability platforms
- Existing infrastructure can be leveraged
- Smaller community and ecosystem than PostgreSQL, MySQL, MongoDB
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, “Elasticsearch vs Qdrant”, https://slateindex.ai/compare/elasticsearch-vs-qdrant, data of Nov 2, 2026. Licence: CC BY 4.0.