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Databases · head to head

Dragonfly vs Qdrant

Dragonfly logo

Dragonfly

Databases

High-performance Redis-compatible in-memory datastore with 25x better throughput

From
Free
Rated
-
Full reviewWebsite
Qdrant logo

Qdrant

Databases

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

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Dragonfly flex tier starting at $36/month may be underpriced, requiring careful usage monitoring; Qdrant free tier extremely limited (0.5 vCPU, 1GB RAM, 4GB disk); suitable only for experiments
  • Prices and features above were last checked on 29 August 2026.

Where they differ

Only the attributes on which Dragonfly and Qdrant actually diverge.

Attributes where Dragonfly and Qdrant differ
AttributeDragonflyQdrant
Pricing modelUsage-based cloud pricing with flexible tiersfreemium
PlatformsCloud, AWS, GCP, AzureCloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming)

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 Dragonfly

  • Redis API compatibility
  • Thread-per-core architecture
  • High-performance caching
  • Memory efficiency
  • Real-time leaderboards
  • Message queue support
  • ML feature serving
  • Cloud deployment

Only in Qdrant

Nothing recorded that Dragonfly does not also cover.

What people use each for

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

Dragonfly

  • High-throughput caching for web applicationsnot Qdrant
  • Real-time leaderboards and rankingsnot Qdrant
  • Message queue and event processingnot Qdrant
  • ML model feature serving at millisecond latenciesnot Qdrant
  • Gaming session state and player data storagenot Qdrant

Qdrant

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

Where each one falls short

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

Dragonfly

  • Flex tier starting at $36/month may be underpriced, requiring careful usage monitoring
  • Business tier $2,000/month represents significant jump in cost
  • Limited to in-memory storage, not suitable for cold data or archival
  • Bring-your-own-cloud requirement on Business tier adds operational complexity
  • Cloud availability dependent on AWS/GCP/Azure uptime

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

Pricing, plan by plan

Dragonfly

Free
  • Free TierFree
    • 100 cloud credits for new signups
    • Equivalent to free trial
  • Business$2000/month
    • Starting price for enterprise offering
    • Bring-your-own-cloud deployment
    • Auto-scaling with custom SLAs
  • Enterprise$undefined/custom
    • Custom pricing
    • Any-cloud deployment
    • Custom instances and sizing

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

Which should you pick?

Choose Dragonfly if

  • You need redis api compatibility.
  • You want to start without paying.
  • You work on Cloud, AWS, GCP, Azure.
  • You also want thread-per-core architecture.
Dragonfly review

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

Questions people ask

Is Dragonfly or Qdrant better?
Neither clearly leads. Dragonfly starts at Free and Qdrant at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dragonfly or Qdrant?
Dragonfly starts at Free and Qdrant at Free.
Does Dragonfly or Qdrant run on more platforms?
Dragonfly runs on Cloud, AWS, GCP, Azure. Qdrant runs on Cloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming).
Can I use Dragonfly for free?
Both have a free tier, so you can try either at no cost before committing.
What is Dragonfly best used for?
Dragonfly is most often used for high-throughput caching for web applications, real-time leaderboards and rankings, message queue and event processing, ml model feature serving at millisecond latencies. Of those, high-throughput caching for web applications and real-time leaderboards and rankings are not what Qdrant is typically brought in for.
What can Dragonfly do that Qdrant cannot?
Dragonfly covers Redis API compatibility, Thread-per-core architecture, High-performance caching, Memory efficiency.

Answered from the vendors’ own pages

Dragonfly: How much faster is Dragonfly than Redis?

Dragonfly achieves 3.97M queries per second compared to Redis's 718K QPS, representing a 25x improvement. Memory efficiency is also 30% better.

Source
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
Dragonfly: Can I migrate from Redis to Dragonfly without code changes?

Yes. Dragonfly maintains full API compatibility with Redis and Memcached, allowing drop-in replacement with minimal to no code modifications.

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
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
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
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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