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Qdrant vs BigQuery

Qdrant logo

Qdrant

Software

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

From
Free
Rated
-
Full reviewWebsite
BigQuery logo

BigQuery

Software

Serverless, highly scalable enterprise data warehouse

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; BigQuery query costs can become substantial for organizations with high query volumes

Where they differ

Only the attributes on which Qdrant and BigQuery actually diverge.

Attributes where Qdrant and BigQuery differ
AttributeQdrantBigQuery
Pricing modelfreemiumusage-based
PlatformsCloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming)Web, Cloud API
FoundedUnknown2008

Identical on both: starting price (Free), 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 BigQuery does not also cover.

Only in BigQuery

  • Serverless Architecture
  • Petabyte Scale
  • Real-time Analytics
  • Machine Learning
  • Geospatial Analysis
  • Streaming Ingestion
  • Standard SQL
  • Looker

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 BigQuery
  • Semantic search across large document corporanot BigQuery
  • Multimodal retrieval (text, images, video) for recommendation systemsnot BigQuery
  • Similarity-based product or content recommendationsnot BigQuery
  • Real-time vector indexing for streaming embedding datanot BigQuery

BigQuery

  • Business intelligencenot Qdrant
  • Data warehousingnot Qdrant
  • Real-time analyticsnot Qdrant
  • Reportingnot Qdrant
  • Machine learningnot 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

BigQuery

  • Query costs can become substantial for organizations with high query volumes
  • Data egress from Google Cloud incurs additional charges

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

BigQuery

Free
  • Free TierFree
    • 1TB queries/month
    • 10GB storage/month
    • Standard support
  • On-demand$6.25/TB
    • Pay per query
    • Pay per storage
    • All features

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 BigQuery if

  • You need serverless architecture.
  • You want to start without paying.
  • You work on Web, Cloud API.
  • You also want petabyte scale.
BigQuery review

Questions people ask

Is Qdrant or BigQuery better?
Neither clearly leads. Qdrant starts at Free and BigQuery at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Qdrant or BigQuery?
Qdrant starts at Free and BigQuery at Free.
Does Qdrant or BigQuery run on more platforms?
Qdrant runs on Cloud (AWS, GCP, Azure), Kubernetes, Self-hosted, Edge (beta), Serverless (coming). BigQuery runs on Web, Cloud API.
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 BigQuery is typically brought in for.
What can Qdrant do that BigQuery cannot?
BigQuery covers Serverless Architecture, Petabyte Scale, Real-time Analytics, Machine Learning.

Answered from the vendors’ own pages

BigQuery: How is BigQuery priced?

BigQuery charges $5 per terabyte of data processed in on-demand queries. Storage is billed separately: active storage is charged per GB, and data inactive for 90+ days moves to long-term storage at reduced rates.

Source
BigQuery: What is BigQuery's architecture?

BigQuery separates compute and storage, using Google's Colossus for distributed storage and Borg for computation, allowing independent scaling of each.

Source
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