Qdrant
Open-source vector database with a free-forever cloud tier and four selectable similarity metrics.
- Vector databases
- Yes
- Not documented
- Standard and Premium tiers run on AWS, Azure and GCP.
Who it suits.
Teams that want a choice of similarity metric rather than one fixed default, or that want the option to self-host the same open-source engine the managed cloud runs.
Consider something else if…
A published, calculator-free entry price matters — Qdrant Cloud's Standard tier pricing is usage-based with no static per-month figure quoted, unlike some competitors' flat entry plans.
Editorial · Palash Bagchi · approved
What the documentation says.
Each value below links to the page it was read from, with the sentence it came from. Criteria Qdrant does not publish are not listed.
Pricing
Free tier
Yes
Sources (1) →Sources ↓
- Qdrant Cloud Pricing ↗
“Free forever. Single Node Cluster: 0.5 vCPU / 1GB RAM / 4 GB Disk. For testing, and prototypes.”
Read 2026-09-11 · official pricing
Pricing model
Usage-based on the Standard tier: billed for compute (vCPU), memory (GB) and storage (GB) consumed by clusters, backup storage, and inference tokens for paid models.
Sources (1) →Sources ↓
- Qdrant Cloud Pricing ↗
“Billing is calculated based on actual resource usage during the billing period. You're charged for compute (vCPU), memory (GB), storage (GB) consumed by your clusters, storage (GB) consumed by backups, and used inference tokens of paid models.”
Read 2026-09-11 · official pricing
Infrastructure
Regions
Standard and Premium tiers run on AWS, Azure and GCP.
Sources (1) →Sources ↓
- Qdrant Cloud Pricing ↗
“AWS, Azure, GCP.”
Read 2026-09-11 · official pricing
Vector
Similarity metrics supported
Dot product, Cosine similarity (implemented as dot-product over automatically normalized vectors), Euclidean distance, and Manhattan distance.
Sources (1) →Sources ↓
- Qdrant documentation ↗
“Dot product (Dot), Cosine similarity (Cosine), Euclidean distance (Euclid), Manhattan distance (Manhattan). Cosine similarity is implemented as dot-product over normalized vectors. Vectors are automatically normalized during upload.”
Read 2026-09-11 · official docs
Metadata filtering
Supported — collections store points (vectors with a payload) and support dedicated filtering on payload fields.
Sources (1) →Sources ↓
- Qdrant documentation ↗
“Points, and vectors with a payload. [...] filtering is available as a search feature.”
Read 2026-09-11 · official docs
When these numbers change, hear about it. Sources are re-checked monthly; a repricing goes out as a short note.