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Databases · head to head

Qdrant vs Zilliz

Qdrant logo

Qdrant

Databases

High-performance vector database for similarity search and embedding-based retrieval

From
Free
Rated
-
Full reviewWebsite
Zilliz logo

Zilliz

Databases

Managed vector database and vector lakebase for AI applications

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Qdrant free tier extremely limited (0.5 vCPU, 1GB RAM, 4GB disk); suitable only for experiments; Zilliz pricing structure not publicly disclosed, requires sales contact

Where they differ

Only the attributes on which Qdrant and Zilliz actually diverge.

Attributes where Qdrant and Zilliz differ
AttributeQdrantZilliz
Pricing modelfreemiumcontact-sales
PlatformsCloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming)Cloud, Self-hosted
FoundedUnknown2017

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Databases).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Qdrant

Nothing recorded that Zilliz does not also cover.

Only in Zilliz

  • Vector indexing
  • Distributed architecture
  • SQL interface
  • Tensor support
  • Real-time search
  • Cloud-native
  • Open-source compatible

What people use each for

The jobs each tool is most often brought in to do.

Qdrant

  • Retrieval-augmented generation (RAG) backends for LLM applicationsnot Zilliz
  • Semantic search across large document corporanot Zilliz
  • Multimodal retrieval (text, images, video) for recommendation systemsnot Zilliz
  • Similarity-based product or content recommendationsnot Zilliz
  • Real-time vector indexing for streaming embedding datanot Zilliz

Zilliz

  • Build retrieval-augmented generation (RAG) systemsnot Qdrant
  • Implement semantic search over documentsnot Qdrant
  • Create multimodal search with text and imagesnot Qdrant
  • Power recommendation engines with vector similaritynot Qdrant
  • Enable similarity search on user embeddingsnot Qdrant

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Qdrant

  • Free tier extremely limited (0.5 vCPU, 1GB RAM, 4GB disk); suitable only for experiments
  • Standard and Premium pricing usage-based; specific costs not published; requires calculator or quote
  • Requires understanding of embeddings and vector search concepts; not suitable for SQL-only teams
  • Early-stage serverless offering (coming soon) suggests maturity gaps in that deployment model

Zilliz

  • Pricing structure not publicly disclosed, requires sales contact
  • Operational complexity for self-hosted Milvus deployments
  • Learning curve for those unfamiliar with vector databases
  • Limited built-in analytics compared to some alternatives

Pricing, plan by plan

Qdrant

Free
  • FreeFree
    • Single-node cluster
    • 0.5 vCPU
    • 1GB RAM
  • Standard$undefined/usage-based
    • Dedicated resources
    • Flexible scaling
    • High availability
  • Premium$undefined/minimum spend
    • SSO and SAML
    • Private VPC links
    • 99.9% uptime SLA

Zilliz

Free

No published plan breakdown. See the Zilliz review.

Which should you pick?

Choose Qdrant if

  • You want to start without paying.
  • You work on Cloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming).
Qdrant review

Choose Zilliz if

  • You need vector indexing.
  • You want to start without paying.
  • You work on Cloud, Self-hosted.
  • You also want distributed architecture.
Zilliz review

Questions people ask

Is Qdrant or Zilliz better?
Neither clearly leads. Qdrant starts at Free and Zilliz at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Qdrant or Zilliz?
Qdrant starts at Free and Zilliz at Free.
Does Qdrant or Zilliz run on more platforms?
Qdrant runs on Cloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming). Zilliz runs on Cloud, Self-hosted.
Can I use Qdrant for free?
Both have a free tier, so you can try either at no cost before committing.
What is Qdrant best used for?
Qdrant is most often used for retrieval-augmented generation (rag) backends for llm applications, semantic search across large document corpora, multimodal retrieval (text, images, video) for recommendation systems, similarity-based product or content recommendations. Of those, retrieval-augmented generation (rag) backends for llm applications and semantic search across large document corpora are not what Zilliz is typically brought in for.
What can Qdrant do that Zilliz cannot?
Zilliz covers Vector indexing, Distributed architecture, SQL interface, Tensor support.

Answered from the vendors’ own pages

Qdrant: Can I use Qdrant for free?

Yes, Qdrant offers a free tier that provides a single node cluster with 0.5 vCPU, 1GB RAM, and 4GB disk space. It includes free cloud inference with selected models and is described as free forever for testing and prototypes.

Source
Zilliz: What is the difference between Milvus and Zilliz Cloud?

Milvus is the open-source vector database that you can self-host. Zilliz Cloud is the fully managed service built on Milvus that removes operational overhead and handles scaling automatically.

Source
Qdrant: How is Qdrant Cloud billing calculated?

Billing is calculated based on actual resource usage during each billing period. You are charged hourly for compute (vCPU), memory (GB), storage (GB), backups, and any paid inference tokens used.

Source
Zilliz: How many vectors can Zilliz handle?

Milvus and Zilliz Cloud can store and search billions of vectors through their distributed architecture that separates storage and compute layers.

Source
Qdrant: What happens if I scale beyond the free tier?

The Standard Tier uses the same usage-based billing model as the free tier but adds features like dedicated resources with flexible scaling, highly available setups with backup and disaster recovery, and a 99.5% uptime SLA.

Source
Zilliz: Is Milvus open-source?

Yes, Milvus is open-source under the Apache License 2.0 and is part of the LF AI & Data Foundation.

Source
Qdrant: What SLA does Qdrant offer?

The Standard Tier provides 99.5% uptime SLA. The Premium Tier, which requires a minimum spend for enterprises, offers 99.9% uptime SLA along with single sign-on and private VPC links.

Source
Zilliz: What pricing does Zilliz Cloud offer?

Zilliz Cloud pricing is not publicly listed and requires contacting their team to discuss your specific scale and use case requirements.

Source
Qdrant: Are there dedicated cloud infrastructure options?

Yes, Qdrant offers Hybrid Cloud (runs on your infrastructure) and Private Cloud (complete isolation) options, both with custom pricing that requires contacting the sales team.

Source
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