Live

Coming soon

Agriculture Tech
Autonomy
Avatars & Digital Humans
Biotech / Synthetic Biology
Blockchain / Crypto
Brain-Computer Interfaces
Climate Tech
Cloud & Edge Computing

Commerce
Cybersecurity
Defense
Digital Identity
Education Tech
Energy
Fashion & Textiles
Food Tech

Healthcare Systems
Longevity & Human Enhancement
Materials Science
Mobility
Quantum Computing
Smart Homes
Space Tech
Wearables

Live

Coming soon

Agriculture Tech
Autonomy
Avatars & Digital Humans
Biotech / Synthetic Biology
Blockchain / Crypto
Brain-Computer Interfaces
Climate Tech
Cloud & Edge Computing

Commerce
Cybersecurity
Defense
Digital Identity
Education Tech
Energy
Fashion & Textiles
Food Tech

Healthcare Systems
Longevity & Human Enhancement
Materials Science
Mobility
Quantum Computing
Smart Homes
Space Tech
Wearables

Qdrant — Vector Databases · fobi

Live

Coming soon

Agriculture Tech
Autonomy
Avatars & Digital Humans
Biotech / Synthetic Biology
Blockchain / Crypto
Brain-Computer Interfaces
Climate Tech
Cloud & Edge Computing

Commerce
Cybersecurity
Defense
Digital Identity
Education Tech
Energy
Fashion & Textiles
Food Tech

Healthcare Systems
Longevity & Human Enhancement
Materials Science
Mobility
Quantum Computing
Smart Homes
Space Tech
Wearables

Qdrant

Qdrant is an open-source vector database optimized for high-dimensional similarity search and filtering on metadata. Raised $28M Series A in 2023. Strong open-source traction. Positioned as the performance-first vector DB for production AI applications.

Written in Rust for performance, Qdrant is a top-three vector database by community adoption and offers advanced filtering that competitors lack.

qdrant.tech Vector Databases

Germanyprivate

At a glance

Total raised

$87.8M

last round series b

Headcount

51-200

approximate · public range

Headquarters

Berlin

Germany

Founded

2021

5 years active

Status

Private

Vector Databases

Subsector

For subscribers

Subscribe to see the full profile

Including Funding rounds, Bull / Bear thesis, Stock + earnings, Roster changes, Patents, News, and Open roles.

Already subscribed? Sign in →

Date	Stage	Amount	Valuation	Lead investors
Mar 12, 2026	Series B	$50M	—	Advance Venture Partners
Jan 23, 2024	Series A	$28M	—	Spark Capital

AI bull / bear

Bull case

Qdrant owns the most defensible technical position in the vector database market. Written in Rust, it benchmarks faster than Go-based competitors like Weaviate and proprietary alternatives like Pinecone on both indexing speed and query latency. Its advanced filtering on metadata — a genuinely hard problem that most vector DBs solve poorly at scale — is the feature that separates production deployments from toy demos. As AI applications move from prototypes to real workloads, teams discover that naive vector search breaks down without rich filtering, and Qdrant is the default answer. The open-source community traction as a top-three vector database creates a self-reinforcing flywheel: more users means more integrations, more bug reports, more edge cases hardened. With only $28M raised, the company has been capital-efficient while competitors burn large war chests on sales-driven growth. If the vector database market consolidates around two or three winners, Qdrant's performance-first DNA and filtering moat make it the most likely survivor.

Bear case

Qdrant is a niche player in a market that is commoditizing fast. Pinecone raised $138M and has the enterprise sales muscle to lock up the biggest AI workloads before Qdrant can scale its go-to-market. Weaviate and Milvus each have larger open-source communities, which means more ecosystem contributions, more third-party tooling, and lower switching costs away from Qdrant. The existential threat is pgvector: PostgreSQL's native vector extension is good enough for 80% of use cases, and enterprises that already run Postgres will never adopt a standalone vector database. Qdrant's $28M Series A is thin capital to compete against well-funded rivals and encroaching incumbents. Meanwhile, Rust limits the contributor base, making it harder to keep pace with feature velocity in Milvus (C++/Go) or Weaviate (Go). If vector search becomes a feature embedded in existing databases — which every major database vendor is racing to do — Qdrant loses its reason to exist entirely.

Generated by deepseek-v4-flash · June 2, 2026Refreshes quarterly · see disclosures

Qdrant

At a glance

Subscribe to see the full profile

Funding history

How they make money

Founder backgrounds

Andre Zayarni

Andrey Vasnetsov

AI bull / bear

In the news

Watch

Leadership

Products

Qdrant Vector Database (Open Source)

Qdrant Cloud

Open roles

Compare Qdrant with