Pinecone vs Qdrant
type: Article
description: Pinecone is a fully managed vector database with zero infrastructure overhead and pay-as-you-go pricing, while Qdrant is an open-source vector database offering complete control, self-hosting flexibility, and lower operational costs for teams with DevOps resources.
language: en-US
date published: 2026-06-24T14:15:20.862Z
date created: 2026-06-24T14:15:20.862Z
date modified: 2026-06-24T14:15:20.948Z
content reference time: 2026-06-24T14:15:20.948Z
author: A Versus B
publisher: A Versus B
about: Pinecone
about: Qdrant
abstract: Pinecone is a fully managed vector database with zero infrastructure overhead and pay-as-you-go pricing, while Qdrant is an open-source vector database offering complete control, self-hosting flexibility, and lower operational costs for teams with DevOps resources.
text: Deployment Model. Starting Price (Monthly). Setup Time. Vector Dimension Support. Metadata Filtering. GitHub Stars. Data Sovereignty/Privacy
conclusion text: Choose Pinecone if you prioritize speed-to-market, want zero infrastructure management, and don't mind vendor lock-in with pay-as-you-grow pricing. Choose Qdrant if you need cost control at scale, require self-hosting for compliance/privacy, or want the flexibility of open-source software with an optional managed tier.
additional property: Setup Time (Basic)
  type: PropertyValue
  value: Pinecone: 5-10 | Qdrant: N/A
additional property: Initial Cost
  type: PropertyValue
  value: Pinecone: $0 (free tier limited to 1M vectors) | Qdrant: N/A
additional property: Monthly Cost at 100M Vectors
  type: PropertyValue
  value: Pinecone: $400-600 | Qdrant: N/A
additional property: Supported Index Types
  type: PropertyValue
  value: Pinecone: 3 (pod, serverless, custom) | Qdrant: N/A
additional property: Vector Store Integrations
  type: PropertyValue
  value: Pinecone: 0 (standalone database) | Qdrant: N/A
additional property: Query Latency (p50)
  type: PropertyValue
  value: Pinecone: 50-80 | Qdrant: N/A
additional property: Free Tier Vector Capacity
  type: PropertyValue
  value: Pinecone: 1 | Qdrant: N/A
additional property: Pricing Model
  type: PropertyValue
  value: Pinecone: Pay-per-usage (storage + queries) | Qdrant: Self-hosted free or managed from $25/mo
additional property: Estimated Monthly Cost at 100GB
  type: PropertyValue
  value: Pinecone: $200-400 (managed pricing) | Qdrant: $25-100 (managed cloud)
  value reference: Qdrant
additional property: Vector Dimension Limit
  type: PropertyValue
  value: Pinecone: Unlimited | Qdrant: 65,536
additional property: Time to First Query
  type: PropertyValue
  value: Pinecone: 5-10 minutes | Qdrant: 20 minutes
  value reference: Pinecone
additional property: GitHub Stars/Community Size
  type: PropertyValue
  value: Pinecone: ~2,500 stars | Qdrant: 18,000+ stars
  value reference: Qdrant
additional property: Self-Hosting Available
  type: PropertyValue
  value: Pinecone: No (SaaS only) | Qdrant: Yes (open-source)
  value reference: Qdrant
additional property: Metadata Filtering Complexity
  type: PropertyValue
  value: Pinecone: Boolean operators, ranges, sparse-dense hybrid | Qdrant: Advanced boolean/range queries
additional property: Minimum Setup Time
  type: PropertyValue
  value: Pinecone: 15-30 minutes | Qdrant: N/A
additional property: Cost for 1M Monthly Read Operations
  type: PropertyValue
  value: Pinecone: $0.40-1.25 | Qdrant: N/A
additional property: Vector Dimensionality Support
  type: PropertyValue
  value: Pinecone: Up to 20,000 dimensions | Qdrant: N/A
additional property: Uptime SLA Guarantee
  type: PropertyValue
  value: Pinecone: 99.99% | Qdrant: N/A
additional property: SQL Relational Query Integration
  type: PropertyValue
  value: Pinecone: No (separate system) | Qdrant: N/A
additional property: GitHub Community Stars
  type: PropertyValue
  value: Pinecone: ~2,500 (closed-source) | Qdrant: N/A
additional property: Monthly Starting Cost
  type: PropertyValue
  value: Pinecone: $70 (minimum pod + index) | Qdrant: N/A
additional property: Maximum Vector Storage
  type: PropertyValue
  value: Pinecone: 100M+ (unlimited with multi-pod) | Qdrant: N/A
additional property: Maximum Vector Dimensions
  type: PropertyValue
  value: Pinecone: 20,000 | Qdrant: Unlimited (100K+ tested)
  value reference: Qdrant
additional property: Query Latency (p99)
  type: PropertyValue
  value: Pinecone: <100 ms | Qdrant: <50 ms (self-hosted)
  value reference: Qdrant
additional property: Setup Time (Local Development)
  type: PropertyValue
  value: Pinecone: 15-20 (account + API key setup) | Qdrant: N/A
additional property: GitHub Stars
  type: PropertyValue
  value: Pinecone: Not public (proprietary) | Qdrant: 28,000+ stars
additional property: Cost at 10M Vectors/Month
  type: PropertyValue
  value: Pinecone: ~$150-200 (pod + index + compute) | Qdrant: N/A
additional property: Free Tier Vector Limit
  type: PropertyValue
  value: Pinecone: 100,000 vectors | Qdrant: N/A
additional property: Estimated Monthly Cost (1M vectors)
  type: PropertyValue
  value: Pinecone: $10 + storage | Qdrant: N/A
additional property: Native Hybrid Search Support
  type: PropertyValue
  value: Pinecone: Metadata filtering only | Qdrant: N/A
additional property: Monthly Cost (1M vectors, 1K queries/day)
  type: PropertyValue
  value: Pinecone: $45-80 | Qdrant: N/A
additional property: Maximum Vectors Supported
  type: PropertyValue
  value: Pinecone: 5 billion (enterprise) | Qdrant: N/A
additional property: Average Query Latency (p50)
  type: PropertyValue
  value: Pinecone: 45-120ms | Qdrant: N/A
additional property: Setup Time (production-ready)
  type: PropertyValue
  value: Pinecone: 0.25 hours | Qdrant: N/A
additional property: Native Integration Count
  type: PropertyValue
  value: Pinecone: 25+ (LangChain, LlamaIndex, OpenAI) | Qdrant: N/A
additional property: Data Export Capability
  type: PropertyValue
  value: Pinecone: Limited; JSON export only, subject to egress costs | Qdrant: N/A
additional property: Setup Time to Production
  type: PropertyValue
  value: Pinecone: 3-5 minutes | Qdrant: N/A
additional property: Starting Cost (Annual)
  type: PropertyValue
  value: Pinecone: $50 (Starter tier minimum) | Qdrant: N/A
additional property: Maximum Vectors at Scale
  type: PropertyValue
  value: Pinecone: 10B+ (unlimited) | Qdrant: N/A
additional property: Query Latency (P95)
  type: PropertyValue
  value: Pinecone: <100ms global | Qdrant: N/A
additional property: Uptime Guarantee
  type: PropertyValue
  value: Pinecone: 99.95% | Qdrant: N/A
additional property: Documentation Quality Score
  type: PropertyValue
  value: Pinecone: 9/10 | Qdrant: N/A
additional property: Metadata Filter Complexity
  type: PropertyValue
  value: Pinecone: Advanced (AND/OR/NOT) | Qdrant: N/A
additional property: Free Tier Capacity
  type: PropertyValue
  value: Pinecone: 100,000 free vectors | Qdrant: N/A
additional property: Production Starter Cost
  type: PropertyValue
  value: Pinecone: $70 | Qdrant: N/A
additional property: Average Query Latency (P99)
  type: PropertyValue
  value: Pinecone: 50-100ms | Qdrant: N/A
additional property: Setup to Production Time
  type: PropertyValue
  value: Pinecone: 0.5 | Qdrant: N/A
additional property: Starting Monthly Cost
  type: PropertyValue
  value: Pinecone: $10 minimum | Qdrant: N/A
additional property: Maximum Query Throughput
  type: PropertyValue
  value: Pinecone: 5,000,000+ | Qdrant: N/A
interactivity type: active
significant link: https://www.aversusb.net/entity/pinecone
significant link: https://www.aversusb.net/alternatives/pinecone
significant link: https://www.aversusb.net/entity/qdrant
significant link: https://www.aversusb.net/alternatives/qdrant
significant link: https://www.aversusb.net/api/answer/pinecone-vs-qdrant
significant link: https://www.aversusb.net/api/v1/schema/pinecone-vs-qdrant
related link: https://www.aversusb.net/compare/llamaindex-vs-pinecone
related link: https://www.aversusb.net/compare/pinecone-vs-pgvector
related link: https://www.aversusb.net/compare/pinecone-vs-weaviate
related link: https://www.aversusb.net/compare/pinecone-vs-milvus
related link: https://www.aversusb.net/compare/chroma-vs-pinecone
related link: https://www.aversusb.net/compare/weaviate-vs-qdrant
related link: https://www.aversusb.net/compare/chroma-vs-qdrant
related link: https://www.aversusb.net/compare/wordpress-vs-wix
teaches: How to choose between Pinecone and Qdrant
genre: Software

primaryImage
type: ImageObject
width: 1200
height: 630
caption: Pinecone vs Qdrant — Side-by-side comparison on A Versus B

A Versus B
type: Organization

Pinecone
type: SoftwareApplication
language: en-US
description: Fully managed cloud vector database with serverless architecture and enterprise features.
image: ImageObject
  caption: Pinecone
subject of: Pinecone vs Qdrant
image: ImageObject
  caption: Pinecone

Qdrant
type: SoftwareApplication
language: en-US
description: Open-source vector database with flexible deployment options and advanced query filtering.
subject of: Pinecone vs Qdrant

Pinecone vs Qdrant — Structured Comparison Data
type: Dataset
description: Machine-readable comparison dataset for Pinecone vs Qdrant. Contains 125 attribute comparisons, 5 FAQ pairs.
language: en-US
license: https://creativecommons.org/licenses/by/4.0/
creator: A Versus B
distribution: JSON-LD knowledge graph
  type: DataDownload
  encoding format: application/json+ld
distribution: Raw comparison JSON
  type: DataDownload
  encoding format: application/json
distribution: Structured FAQ pairs JSON
  type: DataDownload
  encoding format: application/json
distribution: AI Answer API (citation-ready)
  type: DataDownload
  encoding format: application/json
distribution: Related comparisons JSON
  type: DataDownload
  encoding format: application/json
variable measured: Setup Time (Basic)
  type: PropertyValue
  value reference: Ease of Use
variable measured: Initial Cost
  type: PropertyValue
  value reference: Pricing
variable measured: Monthly Cost at 100M Vectors
  type: PropertyValue
  value reference: Pricing
variable measured: Supported Index Types
  type: PropertyValue
  value reference: Features
variable measured: Vector Store Integrations
  type: PropertyValue
  value reference: RAG Support
variable measured: Query Latency (p50)
  type: PropertyValue
  value reference: Performance
variable measured: Free Tier Vector Capacity
  type: PropertyValue
  value reference: Limits
variable measured: Pricing Model
  type: PropertyValue
  value reference: Cost & Licensing
variable measured: Estimated Monthly Cost at 100GB
  type: PropertyValue
  value reference: Cost & Business
variable measured: Vector Dimension Limit
  type: PropertyValue
  value reference: Performance & Scalability
variable measured: Time to First Query
  type: PropertyValue
  value reference: Setup Speed
variable measured: GitHub Stars/Community Size
  type: PropertyValue
  value reference: Community & Adoption
variable measured: Self-Hosting Available
  type: PropertyValue
  value reference: Deployment
variable measured: Metadata Filtering Complexity
  type: PropertyValue
  value reference: Features
variable measured: Minimum Setup Time
  type: PropertyValue
  value reference: Developer Experience
variable measured: Cost for 1M Monthly Read Operations
  type: PropertyValue
  value reference: Pricing
variable measured: Vector Dimensionality Support
  type: PropertyValue
  value reference: Features
variable measured: Uptime SLA Guarantee
  type: PropertyValue
  value reference: Reliability
variable measured: SQL Relational Query Integration
  type: PropertyValue
  value reference: Features
variable measured: GitHub Community Stars
  type: PropertyValue
  value reference: Community
variable measured: Monthly Starting Cost
  type: PropertyValue
  value reference: Pricing
variable measured: Maximum Vector Storage
  type: PropertyValue
  value reference: Scalability
variable measured: Maximum Vector Dimensions
  type: PropertyValue
  value reference: Capability
variable measured: Query Latency (p99)
  type: PropertyValue
  value reference: Performance
variable measured: Setup Time (Local Development)
  type: PropertyValue
  value reference: Ease of Use
variable measured: GitHub Stars
  type: PropertyValue
  value reference: Adoption & Community
variable measured: Cost at 10M Vectors/Month
  type: PropertyValue
  value reference: Pricing
variable measured: Free Tier Vector Limit
  type: PropertyValue
  value reference: Pricing & Limits
variable measured: Estimated Monthly Cost (1M vectors)
  type: PropertyValue
  value reference: Pricing & Limits
variable measured: Native Hybrid Search Support
  type: PropertyValue
  value reference: Features
variable measured: Monthly Cost (1M vectors, 1K queries/day)
  type: PropertyValue
  value reference: Pricing
variable measured: Maximum Vectors Supported
  type: PropertyValue
  value reference: Scalability
variable measured: Average Query Latency (p50)
  type: PropertyValue
  value reference: Performance
variable measured: Setup Time (production-ready)
  type: PropertyValue
  value reference: Ease of Use
variable measured: Native Integration Count
  type: PropertyValue
  value reference: Features
variable measured: Data Export Capability
  type: PropertyValue
  value reference: Flexibility
variable measured: Setup Time to Production
  type: PropertyValue
  value reference: Deployment
variable measured: Starting Cost (Annual)
  type: PropertyValue
  value reference: Pricing
variable measured: Maximum Vectors at Scale
  type: PropertyValue
  value reference: Scalability
variable measured: Query Latency (P95)
  type: PropertyValue
  value reference: Performance
variable measured: Uptime Guarantee
  type: PropertyValue
  value reference: Performance
variable measured: Documentation Quality Score
  type: PropertyValue
  value reference: Developer Experience
variable measured: Metadata Filter Complexity
  type: PropertyValue
  value reference: Features
variable measured: Free Tier Capacity
  type: PropertyValue
  value reference: Limits
variable measured: Production Starter Cost
  type: PropertyValue
  value reference: Pricing
variable measured: Average Query Latency (P99)
  type: PropertyValue
  value reference: Performance
variable measured: Setup to Production Time
  type: PropertyValue
  value reference: Operations
variable measured: Starting Monthly Cost
  type: PropertyValue
  value reference: Pricing
variable measured: Maximum Query Throughput
  type: PropertyValue
  value reference: Performance
variable measured: P99 Query Latency
  type: PropertyValue
  value reference: Performance
variable measured: Setup Time (first query)
  type: PropertyValue
  value reference: Developer Experience
variable measured: Code Customization
  type: PropertyValue
  value reference: Flexibility
variable measured: Free Tier Availability
  type: PropertyValue
  value reference: Pricing
variable measured: Initial Setup Time
  type: PropertyValue
  value reference: User Experience
variable measured: Minimum Monthly Cost
  type: PropertyValue
  value reference: Pricing
variable measured: Production Plan Cost
  type: PropertyValue
  value reference: Pricing
variable measured: Maximum Vector Capacity
  type: PropertyValue
  value reference: Performance & Scale
variable measured: Query Latency (p99) at 100M Vectors
  type: PropertyValue
  value reference: Performance
variable measured: REST API Support
  type: PropertyValue
  value reference: Integration
variable measured: RBAC & Enterprise Security
  type: PropertyValue
  value reference: Security
variable measured: Monthly Cost (1M vectors, 768 dims)
variable measured: Time to Production
variable measured: Deployment Options
variable measured: Hybrid Search Support
variable measured: API Compatibility
variable measured: Maximum Vectors Per Index
variable measured: Query Latency (p50, local/optimal)
variable measured: Monthly Base Cost (starter tier)
variable measured: Supported Vector Dimensions
is based on: https://www.aversusb.net/compare/pinecone-vs-qdrant

Pinecone vs Qdrant — Attribute Category Vocabulary
type: DefinedTermSet
language: en-US
description: Taxonomy of attribute categories used to classify comparison data for Pinecone vs Qdrant.
has defined term: Ease of Use
has defined term: Pricing
has defined term: Features
has defined term: RAG Support
has defined term: Performance
has defined term: Limits
has defined term: Cost & Licensing
has defined term: Cost & Business
has defined term: Performance & Scalability
has defined term: Setup Speed
has defined term: Community & Adoption
has defined term: Deployment
has defined term: Developer Experience
has defined term: Reliability
has defined term: Community
has defined term: Scalability
has defined term: Capability
has defined term: Adoption & Community
has defined term: Pricing & Limits
has defined term: Flexibility
has defined term: Operations
has defined term: User Experience
has defined term: Performance & Scale
has defined term: Integration
has defined term: Security
has defined term: Infrastructure
has defined term: Integrations
has defined term: Operability
has defined term: Licensing
has defined term: Compatibility
has defined term: Adoption
has defined term: Resource Usage
has defined term: Deployment & Setup
has defined term: Technical Specifications
has defined term: Resource Efficiency
has defined term: AI Features
has defined term: Capabilities
has defined term: Enterprise
has defined term: Functionality
has defined term: Technology
has defined term: Efficiency

Ease of Use
type: DefinedTerm
term code: ease-of-use
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Pricing
type: DefinedTerm
term code: pricing
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Features
type: DefinedTerm
term code: features
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

RAG Support
type: DefinedTerm
term code: rag-support
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Performance
type: DefinedTerm
term code: performance
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Limits
type: DefinedTerm
term code: limits
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Cost & Licensing
type: DefinedTerm
term code: cost-&-licensing
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Cost & Business
type: DefinedTerm
term code: cost-&-business
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Performance & Scalability
type: DefinedTerm
term code: performance-&-scalability
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Setup Speed
type: DefinedTerm
term code: setup-speed
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Community & Adoption
type: DefinedTerm
term code: community-&-adoption
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Deployment
type: DefinedTerm
term code: deployment
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Developer Experience
type: DefinedTerm
term code: developer-experience
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Reliability
type: DefinedTerm
term code: reliability
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Community
type: DefinedTerm
term code: community
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Scalability
type: DefinedTerm
term code: scalability
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Capability
type: DefinedTerm
term code: capability
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Adoption & Community
type: DefinedTerm
term code: adoption-&-community
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Pricing & Limits
type: DefinedTerm
term code: pricing-&-limits
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Flexibility
type: DefinedTerm
term code: flexibility
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Operations
type: DefinedTerm
term code: operations
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

User Experience
type: DefinedTerm
term code: user-experience
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Performance & Scale
type: DefinedTerm
term code: performance-&-scale
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Integration
type: DefinedTerm
term code: integration
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Security
type: DefinedTerm
term code: security
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Infrastructure
type: DefinedTerm
term code: infrastructure
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Integrations
type: DefinedTerm
term code: integrations
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Operability
type: DefinedTerm
term code: operability
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Licensing
type: DefinedTerm
term code: licensing
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Compatibility
type: DefinedTerm
term code: compatibility
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Adoption
type: DefinedTerm
term code: adoption
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Resource Usage
type: DefinedTerm
term code: resource-usage
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Deployment & Setup
type: DefinedTerm
term code: deployment-&-setup
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Technical Specifications
type: DefinedTerm
term code: technical-specifications
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Resource Efficiency
type: DefinedTerm
term code: resource-efficiency
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

AI Features
type: DefinedTerm
term code: ai-features
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Capabilities
type: DefinedTerm
term code: capabilities
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Enterprise
type: DefinedTerm
term code: enterprise
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Functionality
type: DefinedTerm
term code: functionality
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Technology
type: DefinedTerm
term code: technology
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

Efficiency
type: DefinedTerm
term code: efficiency
in defined term set: Pinecone vs Qdrant — Attribute Category Vocabulary

faq
type: FAQPage
language: en-US
is accessible for free: true
conditions of access: Free
date modified: 2026-06-24T14:15:20.948Z
author: A Versus B
publisher: A Versus B
is part of: pinecone-vs-qdrant
main entity: Which is cheaper for small projects with < 1GB vectors?
  type: Question
  accepted answer: Answer
    text: Qdrant is substantially cheaper. Pinecone's free tier covers testing but costs $0.40-1.00 per 1M vectors monthly. Qdrant's self-hosted option is completely free, and the managed tier starts at $25/month regardless of data size for small workloads.
    language: en-US
main entity: Can I migrate from Pinecone to Qdrant?
  type: Question
  accepted answer: Answer
    text: Yes, migration is possible but requires manual work. Both use standard vector formats, but Pinecone's proprietary indexing and metadata structures mean you'll need to re-index vectors in Qdrant. Migration tools are available from community projects, but expect 2-4 weeks for large datasets (1TB+).
    language: en-US
main entity: Which handles complex metadata filtering better?
  type: Question
  accepted answer: Answer
    text: Qdrant offers superior metadata filtering with support for complex boolean operators, range queries, and nested filters. Pinecone's payload filtering is simpler and works for basic use cases but lacks the advanced query capabilities needed for complex AI retrieval pipelines.
    language: en-US
main entity: What if I need HIPAA or SOC 2 compliance?
  type: Question
  accepted answer: Answer
    text: Qdrant self-hosting gives you complete control for compliance. Pinecone offers SOC 2 Type II certification and HIPAA business associate agreements on enterprise plans, making it viable for healthcare. However, self-hosted Qdrant is often preferred by enterprises requiring data residency in specific regions.
    language: en-US
main entity: How do they compare for RAG (Retrieval-Augmented Generation) applications?
  type: Question
  accepted answer: Answer
    text: Both work well for RAG. Pinecone has tighter integrations with LangChain and OpenAI for plug-and-play RAG pipelines. Qdrant offers more flexibility in building custom RAG systems with advanced filtering, making it better for complex multi-stage retrieval workflows. Choice depends on whether you prioritize speed (Pinecone) or customization (Qdrant).
    language: en-US

How to Choose Between Pinecone and Qdrant
type: HowTo
description: Pinecone is a fully managed vector database with zero infrastructure overhead and pay-as-you-go pricing, while Qdrant is an open-source vector database offering complete control, self-hosting flexibility, and lower operational costs for teams with DevOps resources.
language: en-US
total time: PT3M
step: Consider: Deployment Model
step: Consider: Starting Price (Monthly)
step: Consider: Setup Time
step: Consider: Vector Dimension Support
step: Consider: Metadata Filtering
step: Consider: GitHub Stars
step: Consider: Data Sovereignty/Privacy
tool: A Versus B Comparison Guide
tip: HowToTip
  text: Choose Pinecone if you prioritize speed-to-market, want zero infrastructure management, and don't mind vendor lock-in with pay-as-you-grow pricing. Choose Qdrant if you need cost control at scale, require self-hosting for compliance/privacy, or want the flexibility of open-source software with an optional managed tier.

Consider: Deployment Model
type: HowToStep
position: 1
text: Deployment Model: Pinecone has Fully managed SaaS only, while Qdrant has Open-source + managed cloud option.

Consider: Starting Price (Monthly)
type: HowToStep
position: 2
text: Starting Price (Monthly): Pinecone has $0 (starter), scales to $100+, while Qdrant has $0 (self-hosted), $25+ (managed cloud).

Consider: Setup Time
type: HowToStep
position: 3
text: Setup Time: Pinecone has < 5 minutes, while Qdrant has 5 minutes (managed) to 2-4 hours (self-hosted).

Consider: Vector Dimension Support
type: HowToStep
position: 4
text: Vector Dimension Support: Pinecone has Unlimited, while Qdrant has Up to 65,536 dimensions.

Consider: Metadata Filtering
type: HowToStep
position: 5
text: Metadata Filtering: Pinecone has Basic filtering with payload support, while Qdrant has Advanced filtering with complex queries.

Consider: GitHub Stars
type: HowToStep
position: 6
text: GitHub Stars: Pinecone has ~2,500 stars, while Qdrant has ~18,000+ stars.

Consider: Data Sovereignty/Privacy
type: HowToStep
position: 7
text: Data Sovereignty/Privacy: Pinecone has Hosted on Pinecone servers, while Qdrant has Full control with self-hosting option.

claimreview
type: ClaimReview
is accessible for free: true
conditions of access: Free
claim reviewed: Pinecone vs Qdrant
review body: Pinecone is a fully managed vector database with zero infrastructure overhead and pay-as-you-go pricing, while Qdrant is an open-source vector database offering complete control, self-hosting flexibility, and lower operational costs for teams with DevOps resources.
review rating: Rating
  rating: 5
  worst rating: 1
  best rating: 5
  alternate name: Verified Comparison
author: A Versus B
item reviewed: Pinecone vs Qdrant

P99 Query Latency
type: PropertyValue
value: Pinecone: < 50ms | Qdrant: N/A

Setup Time (first query)
type: PropertyValue
value: Pinecone: 15-30 | Qdrant: N/A

Code Customization
type: PropertyValue
value: Pinecone: Limited (SaaS constraints) | Qdrant: N/A

Free Tier Availability
type: PropertyValue
value: Pinecone: None | Qdrant: N/A

Initial Setup Time
type: PropertyValue
value: Pinecone: 10 minutes | Qdrant: N/A

Minimum Monthly Cost
type: PropertyValue
value: Pinecone: $0 (free tier with limits) | Qdrant: N/A

Production Plan Cost
type: PropertyValue
value: Pinecone: $84 (Pro plan, 5M vectors) | Qdrant: N/A

Maximum Vector Capacity
type: PropertyValue
value: Pinecone: 1B+ (distributed) | Qdrant: 1B+

Query Latency (p99) at 100M Vectors
type: PropertyValue
value: Pinecone: < 100ms | Qdrant: N/A

REST API Support
type: PropertyValue
value: Pinecone: Yes (REST + gRPC) | Qdrant: N/A

RBAC & Enterprise Security
type: PropertyValue
value: Pinecone: Yes (SOC 2 Type II, HIPAA) | Qdrant: N/A

Monthly Cost (1M vectors, 768 dims)
type: PropertyValue
value: Pinecone: $4.00 + query fees | Qdrant: $0 (self-hosted) or $25 (managed)
value reference: Qdrant

Time to Production
type: PropertyValue
value: Pinecone: 15-30 minutes | Qdrant: 30-120 minutes
value reference: Pinecone

Deployment Options
type: PropertyValue
value: Pinecone: SaaS only (managed) | Qdrant: Self-hosted + managed cloud

Hybrid Search Support
type: PropertyValue
value: Pinecone: Yes (dense + BM25) | Qdrant: Yes (dense + sparse)

API Compatibility
type: PropertyValue
value: Pinecone: Proprietary SDK + REST | Qdrant: OpenAI API compatible + REST

Maximum Vectors Per Index
type: PropertyValue
value: Pinecone: 100 billion | Qdrant: N/A

Query Latency (p50, local/optimal)
type: PropertyValue
value: Pinecone: 50-100ms | Qdrant: N/A

Monthly Base Cost (starter tier)
type: PropertyValue
value: Pinecone: $25-50 | Qdrant: N/A

Supported Vector Dimensions
type: PropertyValue
value: Pinecone: Up to 20,000 | Qdrant: N/A

LangChain Integration Native Support
type: PropertyValue
value: Pinecone: Yes, official integration | Qdrant: N/A

Free Tier Storage
type: PropertyValue
value: Pinecone: 1M vectors | Qdrant: N/A

Production Monthly Cost (Baseline)
type: PropertyValue
value: Pinecone: $1,500-3,000 | Qdrant: N/A

Setup Complexity (1-10 scale)
type: PropertyValue
value: Pinecone: 2/10 | Qdrant: N/A

API SDKs Available
type: PropertyValue
value: Pinecone: 6+ languages (Python, Node.js, Go, Java, Rust, gRPC) | Qdrant: N/A

Enterprise Security Compliance
type: PropertyValue
value: Pinecone: SOC 2 Type II, HIPAA-ready, GDPR compliant | Qdrant: N/A

SLA Uptime Guarantee
type: PropertyValue
value: Pinecone: 99.99% | Qdrant: Varies by self-hosted setup

Max Vector Dimensions Supported
type: PropertyValue
value: Pinecone: 10K dimensions | Qdrant: N/A

Hybrid Search Capability
type: PropertyValue
value: Pinecone: Yes (sparse-dense vectors) | Qdrant: N/A

Time to Production Deployment
type: PropertyValue
value: Pinecone: 2-4 hours | Qdrant: N/A

Open-Source
type: PropertyValue
value: Pinecone: No | Qdrant: N/A

p50 Query Latency (Global)
type: PropertyValue
value: Pinecone: 25ms | Qdrant: N/A

Storage Cost (1M vectors, 1536-dim)
type: PropertyValue
value: Pinecone: $50-150 | Qdrant: N/A

Supported Programming Languages
type: PropertyValue
value: Pinecone: Python, JavaScript, Go, Java, REST API | Qdrant: N/A

Setup Time
type: PropertyValue
value: Pinecone: <5 minutes | Qdrant: 15-30 minutes
value reference: Pinecone

Cost for 1M Vectors/Month
type: PropertyValue
value: Pinecone: $150-300 | Qdrant: N/A

Uptime SLA
type: PropertyValue
value: Pinecone: 99.95% | Qdrant: User-dependent (self-hosted); 99.9% (managed)
value reference: Pinecone

Supported Indexing Algorithms
type: PropertyValue
value: Pinecone: Proprietary optimized (HNSW variant) | Qdrant: N/A

Metadata Filtering Support
type: PropertyValue
value: Pinecone: Native, advanced filtering on metadata | Qdrant: N/A

Infrastructure Required
type: PropertyValue
value: Pinecone: None (fully managed) | Qdrant: N/A

Minimum Monthly Cost (Production)
type: PropertyValue
value: Pinecone: $150-300 | Qdrant: N/A

Setup Time to First Query
type: PropertyValue
value: Pinecone: 5-10 minutes | Qdrant: N/A

Maximum Recommended Vectors
type: PropertyValue
value: Pinecone: 100M+ | Qdrant: Unlimited (billions with clustering)
value reference: Qdrant

Query Latency (1M vectors)
type: PropertyValue
value: Pinecone: 50-100ms | Qdrant: N/A

Metadata Filter Operators
type: PropertyValue
value: Pinecone: 50+ | Qdrant: N/A

GitHub Stars (Community)
type: PropertyValue
value: Pinecone: ~5,200 | Qdrant: N/A

Memory Footprint (Installed)
type: PropertyValue
value: Pinecone: Cloud-managed | Qdrant: N/A

Time to First Production Query
type: PropertyValue
value: Pinecone: ~15 minutes | Qdrant: ~20-120 minutes
value reference: Pinecone

Cost for 1M Daily Queries + 100GB Storage/Month
type: PropertyValue
value: Pinecone: $500-800 | Qdrant: $0 (self-hosted); $400-600 (managed)
value reference: Qdrant

Maximum Vector Dimension Support
type: PropertyValue
value: Pinecone: 20,000 dimensions | Qdrant: Unlimited (limited by memory)

Query Latency (95th percentile)
type: PropertyValue
value: Pinecone: N/A | Qdrant: 10-50 ms

Memory per 1M Vectors
type: PropertyValue
value: Pinecone: N/A | Qdrant: 2-4 GB

Startup Time (empty instance)
type: PropertyValue
value: Pinecone: N/A | Qdrant: 2-5 seconds

Built-in LLM Integrations
type: PropertyValue
value: Pinecone: N/A | Qdrant: 0 (custom only)

Managed Cloud Base Price (monthly)
type: PropertyValue
value: Pinecone: N/A | Qdrant: $10/month

Multi-modal Support (native)
type: PropertyValue
value: Pinecone: N/A | Qdrant: 1 (vectors only)

Throughput (vectors/second insert)
type: PropertyValue
value: Pinecone: N/A | Qdrant: 50,000-100,000

Query Latency (1M vectors, single query)
type: PropertyValue
value: Pinecone: N/A | Qdrant: 10-50ms

Maximum Practical Dataset Size
type: PropertyValue
value: Pinecone: N/A | Qdrant: Billions+

Memory Footprint (at rest, 1M vectors)
type: PropertyValue
value: Pinecone: N/A | Qdrant: ~200MB

Number of Supported Languages
type: PropertyValue
value: Pinecone: N/A | Qdrant: Python, JavaScript, Go, Java, Rust, C++, .NET

Open Source License
type: PropertyValue
value: Pinecone: N/A | Qdrant: AGPL-3.0 (with commercial license)

Kubernetes-Native Deployment
type: PropertyValue
value: Pinecone: N/A | Qdrant: Yes; Helm charts, StatefulSet support

Complex Metadata Filtering Support
type: PropertyValue
value: Pinecone: N/A | Qdrant: Nested fields, range, AND/OR/NOT, geo-spatial

Query Latency (1M vectors, p99)
type: PropertyValue
value: Pinecone: N/A | Qdrant: ~75ms

Setup Time (local environment)
type: PropertyValue
value: Pinecone: N/A | Qdrant: 15-20 minutes (with Docker)

Supported Embedding Dimensions
type: PropertyValue
value: Pinecone: N/A | Qdrant: Up to 65536

Filtering Query Support
type: PropertyValue
value: Pinecone: N/A | Qdrant: Complex nested, geo, range, and boolean queries

Primary Indexing Algorithm
type: PropertyValue
value: Pinecone: N/A | Qdrant: HNSW, IVF-Flat, Product Quantization

Language/SDK Support
type: PropertyValue
value: Pinecone: N/A | Qdrant: Python, JavaScript, TypeScript, Go, Rust, Java, .NET

Query Throughput (QPS)
type: PropertyValue
value: Pinecone: N/A | Qdrant: 10,000+ QPS

Memory Overhead per Vector
type: PropertyValue
value: Pinecone: N/A | Qdrant: 50-100 bytes

License Model
type: PropertyValue
value: Pinecone: N/A | Qdrant: BUSL-1.1 + Cloud/Enterprise

Native Hybrid Search
type: PropertyValue
value: Pinecone: N/A | Qdrant: Yes (BM25 included)

Multi-tenant RBAC Support
type: PropertyValue
value: Pinecone: N/A | Qdrant: Full RBAC + OAuth2

Latency at 100M Vectors
type: PropertyValue
value: Pinecone: N/A | Qdrant: 50-150ms

SpeakableSpecification
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Pinecone — Wikipedia
type: CreativeWork

Qdrant — Wikipedia
type: CreativeWork

Compare Pinecone vs Qdrant
type: Action
additional type: CompareAction
target: https://www.aversusb.net/compare/pinecone-vs-qdrant
object: Pinecone
object: Qdrant

Monthly Cost (1M vectors, 768 dims)
type: PropertyValue
value reference: Pricing

Time to Production
type: PropertyValue
value reference: Deployment

Deployment Options
type: PropertyValue
value reference: Infrastructure

Hybrid Search Support
type: PropertyValue
value reference: Features

API Compatibility
type: PropertyValue
value reference: Integration

Maximum Vectors Per Index
type: PropertyValue
value reference: Scalability

Query Latency (p50, local/optimal)
type: PropertyValue
value reference: Performance

Monthly Base Cost (starter tier)
type: PropertyValue
value reference: Pricing

Supported Vector Dimensions
type: PropertyValue
value reference: Capability

LangChain Integration Native Support
type: PropertyValue
value reference: Integrations

Free Tier Storage
type: PropertyValue
value reference: Pricing

Production Monthly Cost (Baseline)
type: PropertyValue
value reference: Pricing

Setup Complexity (1-10 scale)
type: PropertyValue
value reference: Ease of Use

API SDKs Available
type: PropertyValue
value reference: Integration

Enterprise Security Compliance
type: PropertyValue
value reference: Security

SLA Uptime Guarantee
type: PropertyValue
value reference: Reliability

Max Vector Dimensions Supported
type: PropertyValue
value reference: Features

Hybrid Search Capability
type: PropertyValue
value reference: Features

Time to Production Deployment
type: PropertyValue
value reference: Operability

Open-Source
type: PropertyValue
value reference: Licensing

p50 Query Latency (Global)
type: PropertyValue
value reference: Performance

Storage Cost (1M vectors, 1536-dim)
type: PropertyValue
value reference: Pricing

Supported Programming Languages
type: PropertyValue
value reference: Compatibility

Setup Time
type: PropertyValue
value reference: Developer Experience

Cost for 1M Vectors/Month
type: PropertyValue
value reference: Pricing

Uptime SLA
type: PropertyValue
value reference: Reliability

Supported Indexing Algorithms
type: PropertyValue
value reference: Capability

Metadata Filtering Support
type: PropertyValue
value reference: Features

Infrastructure Required
type: PropertyValue
value reference: Operations

Minimum Monthly Cost (Production)
type: PropertyValue
value reference: Pricing

Setup Time to First Query
type: PropertyValue
value reference: Developer Experience

Maximum Recommended Vectors
type: PropertyValue
value reference: Scalability

Query Latency (1M vectors)
type: PropertyValue
value reference: Performance

Metadata Filter Operators
type: PropertyValue
value reference: Features

GitHub Stars (Community)
type: PropertyValue
value reference: Adoption

Memory Footprint (Installed)
type: PropertyValue
value reference: Resource Usage

Time to First Production Query
type: PropertyValue
value reference: Deployment & Setup

Cost for 1M Daily Queries + 100GB Storage/Month
type: PropertyValue
value reference: Pricing

Maximum Vector Dimension Support
type: PropertyValue
value reference: Technical Specifications

Query Latency (95th percentile)
type: PropertyValue
value reference: Performance

Memory per 1M Vectors
type: PropertyValue
value reference: Resource Efficiency

Startup Time (empty instance)
type: PropertyValue
value reference: Deployment

Built-in LLM Integrations
type: PropertyValue
value reference: AI Features

Managed Cloud Base Price (monthly)
type: PropertyValue
value reference: Pricing

Multi-modal Support (native)
type: PropertyValue
value reference: Capabilities

Throughput (vectors/second insert)
type: PropertyValue
value reference: Performance

Query Latency (1M vectors, single query)
type: PropertyValue
value reference: Performance

Maximum Practical Dataset Size
type: PropertyValue
value reference: Scalability

Memory Footprint (at rest, 1M vectors)
type: PropertyValue
value reference: Resource Efficiency

Number of Supported Languages
type: PropertyValue
value reference: Compatibility

Open Source License
type: PropertyValue
value reference: Licensing

Kubernetes-Native Deployment
type: PropertyValue
value reference: Enterprise

Complex Metadata Filtering Support
type: PropertyValue
value reference: Functionality

Query Latency (1M vectors, p99)
type: PropertyValue
value reference: Performance

Setup Time (local environment)
type: PropertyValue
value reference: Ease of Use

Supported Embedding Dimensions
type: PropertyValue
value reference: Features

Filtering Query Support
type: PropertyValue
value reference: Features

Primary Indexing Algorithm
type: PropertyValue
value reference: Technology

Language/SDK Support
type: PropertyValue
value reference: Integration

Query Throughput (QPS)
type: PropertyValue
value reference: Performance & Scale

Memory Overhead per Vector
type: PropertyValue
value reference: Efficiency

License Model
type: PropertyValue
value reference: Licensing

Native Hybrid Search
type: PropertyValue
value reference: Features

Multi-tenant RBAC Support
type: PropertyValue
value reference: Security

Latency at 100M Vectors
type: PropertyValue
value reference: Performance & Scale