Software · head to head
Qdrant vs Couchbase
Qdrant
Software
High-performance vector database for similarity search and embedding-based retrieval
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Qdrant free tier extremely limited (0.5 vCPU, 1GB RAM, 4GB disk); suitable only for experiments; Couchbase the free tier is a single node with 8 GB of storage and forum support only
Where they differ
Only the attributes on which Qdrant and Couchbase actually diverge.
Identical on both: starting price (Free), pricing model (freemium), free tier (Yes), user rating (Not yet rated), category (Unknown).
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 Couchbase does not also cover.
Only in Couchbase
- JSON Document Model
- SQL++ Query
- Full-text Search
- Eventing
- Analytics
- Mobile Sync
- Multi-dimensional Scaling
- Kafka
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 Couchbase
- Semantic search across large document corporanot Couchbase
- Multimodal retrieval (text, images, video) for recommendation systemsnot Couchbase
- Similarity-based product or content recommendationsnot Couchbase
- Real-time vector indexing for streaming embedding datanot Couchbase
Couchbase
- Running a distributed NoSQL document database as a managed servicenot Qdrant
- Mobile sync and offline first applications backed by a cloud databasenot 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
Couchbase
- The free tier is a single node with 8 GB of storage and forum support only
- Node rates are hourly and quoted as starting figures, from $0.15 an hour on Basic to $0.49 on Enterprise
- The Developer Pro and Enterprise plans require 3 nodes, so the hourly rate multiplies before any usage
- Backup storage is billed separately at $0.07 per GB a month, and analytics backups at $0.14
- Support response time is a plan feature, at 8 hours on Developer Pro against 30 minutes on Enterprise
- AI and analytics run as separately priced planes at up to $0.86 an hour per node
Pricing, plan by plan
Qdrant
Free- FreeFree
- Single-node cluster
- 0.5 vCPU
- 1GB RAM
- Standard$null/usage-based
- Dedicated resources
- Flexible scaling
- High availability
- Premium$null/minimum spend
- SSO and SAML
- Private VPC links
- 99.9% uptime SLA
Couchbase
Free- CommunityFree
- Full features
- Community support
- Self-managed
- Capella FreeFree
- Managed service
- Limited resources
- Cloud hosted
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).
Choose Couchbase if
- You need json document model.
- You want to start without paying.
- You work on Linux, Windows, Mac, Docker, Web.
- You also want sql++ query.
Questions people ask
- Is Qdrant or Couchbase better?
- Neither clearly leads. Qdrant starts at Free and Couchbase at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Qdrant or Couchbase?
- Qdrant starts at Free and Couchbase at Free.
- Does Qdrant or Couchbase run on more platforms?
- Qdrant runs on Cloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming). Couchbase runs on Linux, Windows, Mac, Docker, Web.
- 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 Couchbase is typically brought in for.
- What can Qdrant do that Couchbase cannot?
- Couchbase covers JSON Document Model, SQL++ Query, Full-text Search, Eventing.