Langfuse
Open Source LLM Engineering Platform
Qdrant Cloud Inference
Unify embeddings and vector search across modalities
Updated February 2026
| Langfuse | Qdrant Cloud Inference | |
|---|---|---|
| Rating | 5.0★ | 5.0★ |
| Reviews | 41 | 22 |
| Pros | 18 | 15 |
| FactScore™ | 81.2 | 68.1 |
FactScore™ Comparison
FactScore™ weighs both quality (rating) and popularity (reviews) for a fairer ranking than stars alone.
Pros & Cons
Only in Langfuse — Pros
LLM observability Open source Detailed tracing Monitoring capabilities Cost-effective Easy to integrate Free tier SDK availability Seamless integration Debugging tools Fast iterations Insightful analytics Community engagement Detailed analytics Excellent UI Flexible architecture Open API Robust telemetryBoth tools — Pros
—Only in Qdrant Cloud Inference — Pros
Fast performance Semantic search Excellent documentation Efficient similarity search Scalable Self-hosting AI insights Batch queries Boolean search Cloud subscription plans Developer community Easy integration Intuitive interface Price performance ratio Written in RustOnly in Langfuse — Cons
—Both tools — Cons
—Only in Qdrant Cloud Inference — Cons
—Details
| Langfuse | Qdrant Cloud Inference | |
|---|---|---|
| Categories | AI Infrastructure Tools, AI Metrics and Evaluation | AI Infrastructure Tools, AI Databases |
| Platforms | Web | Web |
| Became Popular | August 20, 2023 | July 16, 2025 |
| Website | langfuse.com | qdrant.tech |
Who Should Pick Which?
Choose Langfuse if...
- LLM observability
- Open source
- Detailed tracing
Choose Qdrant Cloud Inference if...
- Fast performance
- Semantic search
- Excellent documentation
With a FactScore™ of 81.2 vs 68.1, Langfuse leads in community reception. Langfuse uniquely offers LLM observability and Open source, while Qdrant Cloud Inference stands out for Fast performance and Semantic search.
What Users Say
Langfuse
Without Langfuse, we would have been flying blind with our drafting agent. This platform is critical not just for measuring performance, but for understanding exactly what context gets pulled into ...
So excited to see Langfuse go live — we've been a happy user for 4 weeks now. Most detailed latency and analytics in the market. Highly recommend for anyone using complex chains or with user-f...
We’ve been unsung Langfuse for 2 months now. It’s easy to integrate and makes it simpler for us to monitor & debug LLM requests during development and beyond.
Qdrant Cloud Inference
We use Qdrant to store and search high-dimensional vector embeddings of malicious patterns, phishing URLs, and threat indicators. This empowers Truelink to compare new threats against known vectors...
We evaluated a bunch of vector DBs—and Qdrant stood out for its blazing speed, filtering, and hybrid search. It's the unsung hero that lets our AI agents recall and reason across docs, CRMs, and co...
After evaluating a bunch of Vector DBs to be our internal vector DB, we finally closed on QDrant because it was the one that scaled the best and had the best price performance ratio
Related Comparisons
Frequently Asked Questions
Which is better, Langfuse or Qdrant Cloud Inference?
Based on FactScore™, Langfuse leads with a score of 81.2 vs 68.1. Langfuse has a higher rating of 5.0★ compared to 5.0★.
What are the pros of Langfuse compared to Qdrant Cloud Inference?
Langfuse uniquely offers: LLM observability, Open source, Detailed tracing, Monitoring capabilities, Cost-effective.
What are the pros of Qdrant Cloud Inference compared to Langfuse?
Qdrant Cloud Inference uniquely offers: Fast performance, Semantic search, Excellent documentation, Efficient similarity search, Scalable.
Is Langfuse better rated than Qdrant Cloud Inference?
Langfuse is rated 5.0★ from 41 reviews. Qdrant Cloud Inference is rated 5.0★ from 22 reviews.
What is the FactScore™ of Langfuse and Qdrant Cloud Inference?
FactScore™ weighs rating and review volume together. Langfuse scores 81.2 and Qdrant Cloud Inference scores 68.1.
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