Chroma vs Pinecone
type: Article
description: Chroma is a lightweight, open-source vector database optimized for fast local development and embedding storage, while Pinecone is a fully managed cloud-native vector database designed for production-scale similarity search with advanced filtering and guaranteed uptime.
language: en-US
date published: 2026-06-24T15:31:51.325Z
date created: 2026-06-24T15:31:51.325Z
date modified: 2026-06-24T15:31:51.377Z
content reference time: 2026-06-24T15:31:51.377Z
author: A Versus B
publisher: A Versus B
about: Chroma
about: Pinecone
abstract: Chroma is a lightweight, open-source vector database optimized for fast local development and embedding storage, while Pinecone is a fully managed cloud-native vector database designed for production-scale similarity search with advanced filtering and guaranteed uptime.
text: Deployment Model. Maximum Vectors Supported. Uptime SLA. Setup Complexity. Free Tier Cost. Metadata Filtering. Use Case Maturity
conclusion text: Choose Chroma if you're building prototypes, working locally, or prioritize zero infrastructure costs and open-source flexibility. Choose Pinecone if you need production-grade reliability, advanced search capabilities at scale, managed infrastructure, and enterprise SLA guarantees.
additional property: Startup Time to First Query
  type: PropertyValue
  value: Chroma: 5 minutes | Pinecone: N/A
additional property: Max Practical Vector Capacity
  type: PropertyValue
  value: Chroma: 0.1-1B (managed) | Pinecone: N/A
additional property: Query Latency (1M vectors, CPU)
  type: PropertyValue
  value: Chroma: 50-200ms | Pinecone: N/A
additional property: GPU Acceleration
  type: PropertyValue
  value: Chroma: Not available | Pinecone: N/A
additional property: Hosting Flexibility
  type: PropertyValue
  value: Chroma: Managed cloud + local/open-source | Pinecone: N/A
additional property: Learning Curve (hours for LLM RAG)
  type: PropertyValue
  value: Chroma: 0.5-2 hours | Pinecone: N/A
additional property: Production Users at Scale
  type: PropertyValue
  value: Chroma: 500+ | Pinecone: N/A
additional property: Monthly Starting Cost
  type: PropertyValue
  value: Chroma: $0 (free, open-source) | Pinecone: $70 (minimum pod + index)
  value reference: Chroma
additional property: Maximum Vector Storage
  type: PropertyValue
  value: Chroma: ~10M (single instance practical limit) | Pinecone: 100M+ (unlimited with multi-pod)
  value reference: Pinecone
additional property: Query Latency (p99)
  type: PropertyValue
  value: Chroma: 50-200ms | Pinecone: <100 ms
  value reference: Pinecone
additional property: Uptime SLA
  type: PropertyValue
  value: Chroma: None (community) | Pinecone: 99.95%
additional property: Setup Time (Local Development)
  type: PropertyValue
  value: Chroma: 2-5 (pip install + Python) | Pinecone: 15-20 (account + API key setup)
  value reference: Chroma
additional property: Cost at 10M Vectors/Month
  type: PropertyValue
  value: Chroma: $0 (self-hosted only) | Pinecone: ~$150-200 (pod + index + compute)
  value reference: Chroma
additional property: Starting Cost (Annual)
  type: PropertyValue
  value: Chroma: $0 (free) | Pinecone: $50 (Starter tier minimum)
  value reference: Chroma
additional property: Maximum Vectors at Scale
  type: PropertyValue
  value: Chroma: Limited to hardware (~1B) | Pinecone: 10B+ (unlimited)
  value reference: Pinecone
additional property: Uptime Guarantee
  type: PropertyValue
  value: Chroma: No SLA | Pinecone: 99.95%
additional property: Documentation Quality Score
  type: PropertyValue
  value: Chroma: 8/10 | Pinecone: 9/10
  value reference: Pinecone
additional property: Metadata Filter Complexity
  type: PropertyValue
  value: Chroma: Basic ($where) | Pinecone: Advanced (AND/OR/NOT)
  value reference: Pinecone
additional property: Setup Time to Production
  type: PropertyValue
  value: Chroma: 0.1 days (2-4 hours) | Pinecone: 3-5 minutes
  value reference: Chroma
additional property: Query Latency (1M vectors)
  type: PropertyValue
  value: Chroma: 100-300ms | Pinecone: 50-100ms
  value reference: Pinecone
additional property: Embedded Tokenizer Support
  type: PropertyValue
  value: Chroma: Yes (6+ models included) | Pinecone: N/A
additional property: Metadata Filtering Support
  type: PropertyValue
  value: Chroma: Native (full SQL-like support) | Pinecone: Native, advanced filtering on metadata
additional property: GPU Support
  type: PropertyValue
  value: Chroma: Experimental/Limited | Pinecone: N/A
additional property: Memory Usage (10M vectors)
  type: PropertyValue
  value: Chroma: 3-5 GB | Pinecone: N/A
additional property: Query Latency (1M vectors, single query)
  type: PropertyValue
  value: Chroma: 150-300ms | Pinecone: N/A
additional property: Maximum Practical Dataset Size
  type: PropertyValue
  value: Chroma: ~10 million | Pinecone: N/A
additional property: Data Connectors
  type: PropertyValue
  value: Chroma: 0 (manual) | Pinecone: N/A
additional property: Setup Time
  type: PropertyValue
  value: Chroma: 5 minutes | Pinecone: <5 minutes
additional property: LLM Provider Support
  type: PropertyValue
  value: Chroma: External (0 native) | Pinecone: N/A
additional property: Minimum Deployment Size
  type: PropertyValue
  value: Chroma: 50 | Pinecone: N/A
additional property: Retrieval Strategy Types
  type: PropertyValue
  value: Chroma: 1 (similarity search) | Pinecone: N/A
additional property: Storage Backends
  type: PropertyValue
  value: Chroma: 3 (in-memory, SQLite, cloud) | Pinecone: N/A
additional property: Production Observability
  type: PropertyValue
  value: Chroma: Basic logging | Pinecone: N/A
additional property: Query Latency (1M vectors, 768-dim, 10th percentile)
  type: PropertyValue
  value: Chroma: ~50ms | Pinecone: N/A
additional property: Built-in Embedding Generation
  type: PropertyValue
  value: Chroma: Yes (OpenAI, HuggingFace, Ollama) | Pinecone: N/A
additional property: Installation Complexity
  type: PropertyValue
  value: Chroma: 5-10 minutes (Python package) | Pinecone: N/A
additional property: SQL Filtering Capability
  type: PropertyValue
  value: Chroma: JSON metadata filters (limited) | Pinecone: N/A
additional property: GitHub Stars (as of 2026)
  type: PropertyValue
  value: Chroma: 12,000+ stars | Pinecone: N/A
additional property: Supported Index Types
  type: PropertyValue
  value: Chroma: Heuristic Search Algorithm (HNSW) | Pinecone: 3 (pod, serverless, custom)
additional property: Time to First Query
  type: PropertyValue
  value: Chroma: 1-2 minutes | Pinecone: 5-10 minutes
  value reference: Chroma
additional property: Memory Footprint (at rest, 1M vectors)
  type: PropertyValue
  value: Chroma: ~800MB | Pinecone: N/A
additional property: Number of Supported Languages
  type: PropertyValue
  value: Chroma: Python + JavaScript | Pinecone: N/A
additional property: Kubernetes-Native Deployment
  type: PropertyValue
  value: Chroma: Not recommended; in-process only | Pinecone: N/A
additional property: Complex Metadata Filtering Support
  type: PropertyValue
  value: Chroma: Basic equality/contains only | Pinecone: N/A
additional property: Maximum Vectors Per Instance
  type: PropertyValue
  value: Chroma: ~10M | Pinecone: N/A
additional property: Average Query Latency
  type: PropertyValue
  value: Chroma: 10-50ms | Pinecone: N/A
additional property: Hybrid Search Support (BM25 + Vector)
  type: PropertyValue
  value: Chroma: No | Pinecone: N/A
additional property: Multi-Tenancy Support
  type: PropertyValue
  value: Chroma: Not supported | Pinecone: N/A
additional property: Minimum Memory for 1M Vectors
  type: PropertyValue
  value: Chroma: 1-2GB | Pinecone: N/A
interactivity type: active
significant link: https://www.aversusb.net/entity/chroma
significant link: https://www.aversusb.net/alternatives/chroma
significant link: https://www.aversusb.net/entity/pinecone
significant link: https://www.aversusb.net/alternatives/pinecone
significant link: https://www.aversusb.net/api/answer/chroma-vs-pinecone
significant link: https://www.aversusb.net/api/v1/schema/chroma-vs-pinecone
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-qdrant
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-faiss
related link: https://www.aversusb.net/compare/chroma-vs-llamaindex
related link: https://www.aversusb.net/compare/chroma-vs-pgvector
teaches: How to choose between Chroma and Pinecone
genre: Software

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

A Versus B
type: Organization

Chroma
type: SoftwareApplication
language: en-US
description: Open-source vector database optimized for rapid prototyping and lightweight deployments.
subject of: Chroma vs Pinecone

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

Chroma vs Pinecone — Structured Comparison Data
type: Dataset
description: Machine-readable comparison dataset for Chroma vs Pinecone. Contains 180 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: Startup Time to First Query
  type: PropertyValue
  value reference: Developer Experience
variable measured: Max Practical Vector Capacity
  type: PropertyValue
  value reference: Scalability
variable measured: Query Latency (1M vectors, CPU)
  type: PropertyValue
  value reference: Performance
variable measured: GPU Acceleration
  type: PropertyValue
  value reference: Performance
variable measured: Hosting Flexibility
  type: PropertyValue
  value reference: Infrastructure
variable measured: Learning Curve (hours for LLM RAG)
  type: PropertyValue
  value reference: Developer Experience
variable measured: Production Users at Scale
  type: PropertyValue
  value reference: Market Adoption
variable measured: Monthly Starting Cost
  type: PropertyValue
  value reference: Pricing
variable measured: Maximum Vector Storage
  type: PropertyValue
  value reference: Scalability
variable measured: Query Latency (p99)
  type: PropertyValue
  value reference: Performance
variable measured: Uptime SLA
  type: PropertyValue
  value reference: Reliability
variable measured: Setup Time (Local Development)
  type: PropertyValue
  value reference: Ease of Use
variable measured: Cost at 10M Vectors/Month
  type: PropertyValue
  value reference: Pricing
variable measured: Starting Cost (Annual)
  type: PropertyValue
  value reference: Pricing
variable measured: Maximum Vectors at Scale
  type: PropertyValue
  value reference: Scalability
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: Setup Time to Production
  type: PropertyValue
  value reference: Deployment
variable measured: Query Latency (1M vectors)
  type: PropertyValue
  value reference: Performance
variable measured: Embedded Tokenizer Support
  type: PropertyValue
  value reference: Features
variable measured: Metadata Filtering Support
  type: PropertyValue
  value reference: Features
variable measured: GPU Support
  type: PropertyValue
  value reference: Hardware
variable measured: Memory Usage (10M vectors)
  type: PropertyValue
  value reference: Resource Usage
variable measured: Query Latency (1M vectors, single query)
  type: PropertyValue
  value reference: Performance
variable measured: Maximum Practical Dataset Size
  type: PropertyValue
  value reference: Scalability
variable measured: Data Connectors
  type: PropertyValue
  value reference: Integration
variable measured: Setup Time
  type: PropertyValue
  value reference: Developer Experience
variable measured: LLM Provider Support
  type: PropertyValue
  value reference: Integration
variable measured: Minimum Deployment Size
  type: PropertyValue
  value reference: Performance
variable measured: Retrieval Strategy Types
  type: PropertyValue
  value reference: Features
variable measured: Storage Backends
  type: PropertyValue
  value reference: Features
variable measured: Production Observability
  type: PropertyValue
  value reference: DevOps Features
variable measured: Query Latency (1M vectors, 768-dim, 10th percentile)
  type: PropertyValue
  value reference: Performance
variable measured: Built-in Embedding Generation
  type: PropertyValue
  value reference: Features
variable measured: Installation Complexity
  type: PropertyValue
  value reference: Setup
variable measured: SQL Filtering Capability
  type: PropertyValue
  value reference: Querying
variable measured: GitHub Stars (as of 2026)
  type: PropertyValue
  value reference: Community Adoption
variable measured: Supported Index Types
  type: PropertyValue
  value reference: Features
variable measured: Time to First Query
  type: PropertyValue
  value reference: Setup Speed
variable measured: Memory Footprint (at rest, 1M vectors)
  type: PropertyValue
  value reference: Resource Efficiency
variable measured: Number of Supported Languages
  type: PropertyValue
  value reference: Compatibility
variable measured: Kubernetes-Native Deployment
  type: PropertyValue
  value reference: Enterprise
variable measured: Complex Metadata Filtering Support
  type: PropertyValue
  value reference: Functionality
variable measured: Maximum Vectors Per Instance
  type: PropertyValue
  value reference: Scalability
variable measured: Average Query Latency
  type: PropertyValue
  value reference: Performance
variable measured: Hybrid Search Support (BM25 + Vector)
  type: PropertyValue
  value reference: Features
variable measured: Multi-Tenancy Support
  type: PropertyValue
  value reference: Features
variable measured: Minimum Memory for 1M Vectors
  type: PropertyValue
  value reference: Resource Requirements
variable measured: Supported Deployment Modes
  type: PropertyValue
  value reference: Deployment
variable measured: Setup Time (first query)
  type: PropertyValue
  value reference: Developer Experience
variable measured: Max Recommended Vector Count
  type: PropertyValue
  value reference: Scalability
variable measured: Query Filtering Support
  type: PropertyValue
  value reference: Features
variable measured: Multi-Modal Search
  type: PropertyValue
  value reference: Features
variable measured: Kubernetes Support
  type: PropertyValue
  value reference: Container Orchestration
variable measured: Minimum Setup Infrastructure
  type: PropertyValue
  value reference: Deployment
variable measured: LangChain Integration Maturity
  type: PropertyValue
  value reference: Ecosystem
variable measured: ACID Compliance
  type: PropertyValue
  value reference: Reliability
variable measured: Maximum Vector Scale
  type: PropertyValue
  value reference: Performance
variable measured: Minimum Setup Time
  type: PropertyValue
  value reference: Developer Experience
variable measured: Hybrid Search (Vector + Keyword)
variable measured: Multi-Modal Support
variable measured: Enterprise Features (RBAC/Multi-tenancy)
variable measured: GitHub Stars
variable measured: Deployment Options
variable measured: Setup Time (Minutes)
variable measured: Supported Data Sources
variable measured: Query Latency (P95)
variable measured: Maximum Embeddings
is based on: https://www.aversusb.net/compare/chroma-vs-pinecone

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

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

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

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

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

Market Adoption
type: DefinedTerm
term code: market-adoption
in defined term set: Chroma vs Pinecone — Attribute Category Vocabulary

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

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

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

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

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

Hardware
type: DefinedTerm
term code: hardware
in defined term set: Chroma vs Pinecone — Attribute Category Vocabulary

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

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

DevOps Features
type: DefinedTerm
term code: devops-features
in defined term set: Chroma vs Pinecone — Attribute Category Vocabulary

Setup
type: DefinedTerm
term code: setup
in defined term set: Chroma vs Pinecone — Attribute Category Vocabulary

Querying
type: DefinedTerm
term code: querying
in defined term set: Chroma vs Pinecone — Attribute Category Vocabulary

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

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

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

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

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

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

Resource Requirements
type: DefinedTerm
term code: resource-requirements
in defined term set: Chroma vs Pinecone — Attribute Category Vocabulary

Container Orchestration
type: DefinedTerm
term code: container-orchestration
in defined term set: Chroma vs Pinecone — Attribute Category Vocabulary

Ecosystem
type: DefinedTerm
term code: ecosystem
in defined term set: Chroma vs Pinecone — Attribute Category Vocabulary

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

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

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

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

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

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

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

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

Feature
type: DefinedTerm
term code: feature
in defined term set: Chroma vs Pinecone — Attribute Category Vocabulary

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

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

Query Capabilities
type: DefinedTerm
term code: query-capabilities
in defined term set: Chroma vs Pinecone — Attribute Category Vocabulary

Enterprise Features
type: DefinedTerm
term code: enterprise-features
in defined term set: Chroma vs Pinecone — Attribute Category Vocabulary

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

Support
type: DefinedTerm
term code: support
in defined term set: Chroma vs Pinecone — Attribute Category Vocabulary

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

Hardware Optimization
type: DefinedTerm
term code: hardware-optimization
in defined term set: Chroma vs Pinecone — Attribute Category Vocabulary

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

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

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

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

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

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

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

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

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

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

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

faq
type: FAQPage
language: en-US
is accessible for free: true
conditions of access: Free
date modified: 2026-06-24T15:31:51.377Z
author: A Versus B
publisher: A Versus B
is part of: chroma-vs-pinecone
main entity: Can I migrate from Chroma to Pinecone?
  type: Question
  accepted answer: Answer
    text: Yes, migration is possible by exporting vectors and embeddings from Chroma (via Python API) and importing them into Pinecone using their bulk upsert API. Most migrations take 1-2 hours for datasets under 100M vectors. Metadata must be reformatted to match Pinecone's schema during migration.
    language: en-US
main entity: Which is better for RAG applications?
  type: Question
  accepted answer: Answer
    text: For development and testing RAG locally, Chroma is ideal due to zero cost and quick setup. For production RAG systems serving 100+ daily queries, Pinecone wins with its 99.95% uptime, faster retrieval (<100ms), and advanced metadata filtering for precise document filtering. Hybrid approaches (Chroma for dev, Pinecone for prod) are common.
    language: en-US
main entity: Does Chroma work offline?
  type: Question
  accepted answer: Answer
    text: Yes, Chroma is fully offline-capable when running locally or with persistent storage. It requires no external API calls unless you use Chroma's hosted cloud option (Chroma Cloud). Pinecone requires internet connectivity and API authentication for all operations.
    language: en-US
main entity: What's the cost difference at 1 billion vectors?
  type: Question
  accepted answer: Answer
    text: At 1B vectors, Chroma costs $0 (self-hosted hardware costs only, ~$5-20K for servers). Pinecone costs approximately $4,000-12,000/month depending on query volume and pod type (s1/p1/p2). For long-term storage at scale, Chroma's hardware investment becomes competitive after 12-18 months.
    language: en-US
main entity: Which has better enterprise support?
  type: Question
  accepted answer: Answer
    text: Pinecone offers dedicated enterprise support, SLA guarantees, SOC 2 compliance, and HIPAA certification. Chroma is community-supported through GitHub issues and Discord, though commercial support partnerships exist. For enterprise requirements, Pinecone is the only option.
    language: en-US

How to Choose Between Chroma and Pinecone
type: HowTo
description: Chroma is a lightweight, open-source vector database optimized for fast local development and embedding storage, while Pinecone is a fully managed cloud-native vector database designed for production-scale similarity search with advanced filtering and guaranteed uptime.
language: en-US
total time: PT3M
step: Consider: Deployment Model
step: Consider: Maximum Vectors Supported
step: Consider: Uptime SLA
step: Consider: Setup Complexity
step: Consider: Free Tier Cost
step: Consider: Metadata Filtering
step: Consider: Use Case Maturity
tool: A Versus B Comparison Guide
tip: HowToTip
  text: Choose Chroma if you're building prototypes, working locally, or prioritize zero infrastructure costs and open-source flexibility. Choose Pinecone if you need production-grade reliability, advanced search capabilities at scale, managed infrastructure, and enterprise SLA guarantees.

Consider: Deployment Model
type: HowToStep
position: 1
text: Deployment Model: Chroma has Open-source, self-hosted or in-memory, while Pinecone has Managed SaaS cloud platform.

Consider: Maximum Vectors Supported
type: HowToStep
position: 2
text: Maximum Vectors Supported: Chroma has Unlimited (limited by hardware), while Pinecone has Millions to billions depending on tier.

Consider: Uptime SLA
type: HowToStep
position: 3
text: Uptime SLA: Chroma has No SLA guarantee, while Pinecone has 99.95% uptime SLA.

Consider: Setup Complexity
type: HowToStep
position: 4
text: Setup Complexity: Chroma has Minutes for local setup, while Pinecone has Minutes for cloud setup, no infrastructure management.

Consider: Free Tier Cost
type: HowToStep
position: 5
text: Free Tier Cost: Chroma has Free (open-source), while Pinecone has $0 starter tier with 100K vectors.

Consider: Metadata Filtering
type: HowToStep
position: 6
text: Metadata Filtering: Chroma has Basic filtering with $where clauses, while Pinecone has Advanced filtering with complex boolean logic.

Consider: Use Case Maturity
type: HowToStep
position: 7
text: Use Case Maturity: Chroma has Best for prototyping and small projects, while Pinecone has Production-ready for enterprise applications.

claimreview
type: ClaimReview
is accessible for free: true
conditions of access: Free
claim reviewed: Chroma vs Pinecone
review body: Chroma is a lightweight, open-source vector database optimized for fast local development and embedding storage, while Pinecone is a fully managed cloud-native vector database designed for production-scale similarity search with advanced filtering and guaranteed uptime.
review rating: Rating
  rating: 5
  worst rating: 1
  best rating: 5
  alternate name: Verified Comparison
author: A Versus B
item reviewed: Chroma vs Pinecone

Supported Deployment Modes
type: PropertyValue
value: Chroma: In-process, SQLite, HTTP API | Pinecone: N/A

Setup Time (first query)
type: PropertyValue
value: Chroma: 2-5 | Pinecone: 15-30
value reference: Chroma

Max Recommended Vector Count
type: PropertyValue
value: Chroma: 1-10M (single node) | Pinecone: N/A

Query Filtering Support
type: PropertyValue
value: Chroma: Basic metadata filters | Pinecone: N/A

Multi-Modal Search
type: PropertyValue
value: Chroma: Text embeddings only | Pinecone: N/A

Kubernetes Support
type: PropertyValue
value: Chroma: Not native; runs as Python process | Pinecone: N/A

Minimum Setup Infrastructure
type: PropertyValue
value: Chroma: Python 3.7+; runs on laptop or serverless | Pinecone: N/A

LangChain Integration Maturity
type: PropertyValue
value: Chroma: Official, first-class integration | Pinecone: N/A

ACID Compliance
type: PropertyValue
value: Chroma: No | Pinecone: N/A

Maximum Vector Scale
type: PropertyValue
value: Chroma: 10-50 million | Pinecone: N/A

Minimum Setup Time
type: PropertyValue
value: Chroma: 2-5 minutes | Pinecone: 15-30 minutes
value reference: Chroma

Hybrid Search (Vector + Keyword)
type: PropertyValue
value: Chroma: No | Pinecone: N/A

Multi-Modal Support
type: PropertyValue
value: Chroma: Text only | Pinecone: N/A

Enterprise Features (RBAC/Multi-tenancy)
type: PropertyValue
value: Chroma: No | Pinecone: N/A

GitHub Stars
type: PropertyValue
value: Chroma: 12,500+ | Pinecone: Not public (proprietary)

Deployment Options
type: PropertyValue
value: Chroma: Embedded, Python, Serverless (SaaS beta) | Pinecone: SaaS only (managed)

Setup Time (Minutes)
type: PropertyValue
value: Chroma: 15-30 | Pinecone: N/A

Supported Data Sources
type: PropertyValue
value: Chroma: 12 embedding models | Pinecone: N/A

Query Latency (P95)
type: PropertyValue
value: Chroma: 45-120 | Pinecone: <100ms global
value reference: Pinecone

Maximum Embeddings
type: PropertyValue
value: Chroma: 50M (in-memory) | Pinecone: N/A

LLM Integration
type: PropertyValue
value: Chroma: Manual (requires wrapper code) | Pinecone: N/A

Learning Curve (Hours)
type: PropertyValue
value: Chroma: 2-4 | Pinecone: N/A

Production Deployments Reported
type: PropertyValue
value: Chroma: 500+ | Pinecone: N/A

Deployment Complexity
type: PropertyValue
value: Chroma: 2/10 | Pinecone: N/A

Initial Setup Time
type: PropertyValue
value: Chroma: 2 minutes | Pinecone: 10 minutes
value reference: Chroma

Minimum Monthly Cost
type: PropertyValue
value: Chroma: $0 (open-source) | Pinecone: $0 (free tier with limits)

Production Plan Cost
type: PropertyValue
value: Chroma: $0 (self-hosted infrastructure only) | Pinecone: $84 (Pro plan, 5M vectors)
value reference: Chroma

Maximum Vector Capacity
type: PropertyValue
value: Chroma: 10M (single machine limit) | Pinecone: 1B+ (distributed)
value reference: Pinecone

Query Latency (p99) at 100M Vectors
type: PropertyValue
value: Chroma: Not tested (infeasible) | Pinecone: < 100ms

REST API Support
type: PropertyValue
value: Chroma: No (client libraries only) | Pinecone: Yes (REST + gRPC)

RBAC & Enterprise Security
type: PropertyValue
value: Chroma: No | Pinecone: Yes (SOC 2 Type II, HIPAA)

Maximum Vectors Per Index
type: PropertyValue
value: Chroma: ~10 million | Pinecone: 100 billion
value reference: Pinecone

Query Latency (p50, local/optimal)
type: PropertyValue
value: Chroma: 5-20ms | Pinecone: 50-100ms
value reference: Chroma

Monthly Base Cost (starter tier)
type: PropertyValue
value: Chroma: $0 (open-source) | Pinecone: $25-50
value reference: Chroma

Supported Vector Dimensions
type: PropertyValue
value: Chroma: Unlimited | Pinecone: Up to 20,000

LangChain Integration Native Support
type: PropertyValue
value: Chroma: Yes, official integration | Pinecone: Yes, official integration

Single-Vector Search Latency (1M vectors)
type: PropertyValue
value: Chroma: 15-25ms | Pinecone: N/A

Maximum Supported Vector Dimensions
type: PropertyValue
value: Chroma: 2048 | Pinecone: N/A

Native SQL Support
type: PropertyValue
value: Chroma: Limited (metadata filtering only) | Pinecone: N/A

Embedding Auto-Generation
type: PropertyValue
value: Chroma: Yes (Hugging Face, OpenAI, etc.) | Pinecone: N/A

Open Source Availability
type: PropertyValue
value: Chroma: Yes (Apache 2.0) | Pinecone: N/A

Managed Cloud Cost (1M queries/month)
type: PropertyValue
value: Chroma: $50-150 | Pinecone: N/A

Relational Data Integration
type: PropertyValue
value: Chroma: No (requires external database) | Pinecone: N/A

Query Latency (1M vectors, p99)
type: PropertyValue
value: Chroma: ~350ms | Pinecone: N/A

Maximum Recommended Vectors
type: PropertyValue
value: Chroma: 10M | Pinecone: 100M+
value reference: Pinecone

Setup Time (local environment)
type: PropertyValue
value: Chroma: 2-3 minutes | Pinecone: N/A

Supported Embedding Dimensions
type: PropertyValue
value: Chroma: Up to 2048 | Pinecone: N/A

Filtering Query Support
type: PropertyValue
value: Chroma: Basic metadata matching | Pinecone: N/A

Primary Indexing Algorithm
type: PropertyValue
value: Chroma: Flat, approximate nearest neighbor | Pinecone: N/A

Language/SDK Support
type: PropertyValue
value: Chroma: Python, JavaScript, Go | Pinecone: N/A

Time to Production (First Query)
type: PropertyValue
value: Chroma: 7 minutes | Pinecone: N/A

Maximum Recommended Vector Count
type: PropertyValue
value: Chroma: ~10M vectors | Pinecone: N/A

Minimum RAM Requirement (Single Node)
type: PropertyValue
value: Chroma: 64 MB | Pinecone: N/A

Advanced Filtering Support
type: PropertyValue
value: Chroma: Basic metadata filters only | Pinecone: N/A

Multi-Tenancy
type: PropertyValue
value: Chroma: Not supported | Pinecone: N/A

Open Source License
type: PropertyValue
value: Chroma: Apache 2.0 (Fully Open) | Pinecone: N/A

Enterprise Support SLA
type: PropertyValue
value: Chroma: Community-driven, no SLA | Pinecone: N/A

Setup Time (minutes to first working example)
type: PropertyValue
value: Chroma: 3 minutes | Pinecone: N/A

Maximum Vector Capacity (single instance)
type: PropertyValue
value: Chroma: 10 million | Pinecone: N/A

Query Latency at 1M vectors
type: PropertyValue
value: Chroma: 50-150ms | Pinecone: N/A

Memory per Million Vectors
type: PropertyValue
value: Chroma: 1.5-2.0 GB | Pinecone: N/A

Built-in Embedding Model Support
type: PropertyValue
value: Chroma: OpenAI, Cohere, Hugging Face, Ollama (6+ providers) | Pinecone: N/A

Index Type Options
type: PropertyValue
value: Chroma: 2 (SQLite, DuckDB) | Pinecone: N/A

GPU Acceleration Support
type: PropertyValue
value: Chroma: No | Pinecone: N/A

p50 Query Latency (Global)
type: PropertyValue
value: Chroma: 250ms (cloud-hosted) | Pinecone: 25ms
value reference: Pinecone

Storage Cost (1M vectors, 1536-dim)
type: PropertyValue
value: Chroma: $0 | Pinecone: $50-150
value reference: Chroma

Metadata Filtering Complexity
type: PropertyValue
value: Chroma: Basic equality/contains | Pinecone: Boolean operators, ranges, sparse-dense hybrid

Supported Programming Languages
type: PropertyValue
value: Chroma: Python, JavaScript, Go, Rust | Pinecone: Python, JavaScript, Go, Java, REST API
value reference: Pinecone

Setup Time to First Query
type: PropertyValue
value: Chroma: 2-3 minutes | Pinecone: 5-10 minutes
value reference: Chroma

Average Latency (1M vectors)
type: PropertyValue
value: Chroma: 75ms | Pinecone: N/A

Maximum Vector Dimensions
type: PropertyValue
value: Chroma: Unlimited | Pinecone: 20,000

SQL Query Support
type: PropertyValue
value: Chroma: No (metadata filters only) | Pinecone: N/A

GitHub Stars (2026)
type: PropertyValue
value: Chroma: 12,000+ | Pinecone: N/A

Minimum Monthly Cost (Production)
type: PropertyValue
value: Chroma: $0 (self-hosted) | Pinecone: $150-300
value reference: Chroma

Metadata Filter Operators
type: PropertyValue
value: Chroma: 10+ | Pinecone: 50+
value reference: Pinecone

GitHub Stars (Community)
type: PropertyValue
value: Chroma: ~15,000+ | Pinecone: ~5,200
value reference: Chroma

Memory Footprint (Installed)
type: PropertyValue
value: Chroma: 15MB | Pinecone: Cloud-managed

Setup Time (Basic)
type: PropertyValue
value: Chroma: N/A | Pinecone: 5-10

Initial Cost
type: PropertyValue
value: Chroma: N/A | Pinecone: $0 (free tier limited to 1M vectors)

Monthly Cost at 100M Vectors
type: PropertyValue
value: Chroma: N/A | Pinecone: $400-600

Vector Store Integrations
type: PropertyValue
value: Chroma: N/A | Pinecone: 0 (standalone database)

Query Latency (p50)
type: PropertyValue
value: Chroma: N/A | Pinecone: 50-80

Free Tier Vector Capacity
type: PropertyValue
value: Chroma: N/A | Pinecone: 1

Pricing Model
type: PropertyValue
value: Chroma: N/A | Pinecone: Pay-per-usage (storage + queries)

Estimated Monthly Cost at 100GB
type: PropertyValue
value: Chroma: N/A | Pinecone: $200-400 (managed pricing)

Vector Dimension Limit
type: PropertyValue
value: Chroma: N/A | Pinecone: Unlimited

GitHub Stars/Community Size
type: PropertyValue
value: Chroma: N/A | Pinecone: ~2,500 stars

Self-Hosting Available
type: PropertyValue
value: Chroma: N/A | Pinecone: No (SaaS only)

Cost for 1M Monthly Read Operations
type: PropertyValue
value: Chroma: N/A | Pinecone: $0.40-1.25

Vector Dimensionality Support
type: PropertyValue
value: Chroma: N/A | Pinecone: Up to 20,000 dimensions

Uptime SLA Guarantee
type: PropertyValue
value: Chroma: N/A | Pinecone: 99.99%

SQL Relational Query Integration
type: PropertyValue
value: Chroma: N/A | Pinecone: No (separate system)

GitHub Community Stars
type: PropertyValue
value: Chroma: N/A | Pinecone: ~2,500 (closed-source)

Free Tier Vector Limit
type: PropertyValue
value: Chroma: N/A | Pinecone: 100,000 vectors

Estimated Monthly Cost (1M vectors)
type: PropertyValue
value: Chroma: N/A | Pinecone: $10 + storage

Native Hybrid Search Support
type: PropertyValue
value: Chroma: N/A | Pinecone: Metadata filtering only

Monthly Cost (1M vectors, 1K queries/day)
type: PropertyValue
value: Chroma: N/A | Pinecone: $45-80

Maximum Vectors Supported
type: PropertyValue
value: Chroma: N/A | Pinecone: 5 billion (enterprise)

Average Query Latency (p50)
type: PropertyValue
value: Chroma: N/A | Pinecone: 45-120ms

Setup Time (production-ready)
type: PropertyValue
value: Chroma: N/A | Pinecone: 0.25 hours

Native Integration Count
type: PropertyValue
value: Chroma: N/A | Pinecone: 25+ (LangChain, LlamaIndex, OpenAI)

Data Export Capability
type: PropertyValue
value: Chroma: N/A | Pinecone: Limited; JSON export only, subject to egress costs

Free Tier Capacity
type: PropertyValue
value: Chroma: N/A | Pinecone: 100,000 free vectors

Production Starter Cost
type: PropertyValue
value: Chroma: N/A | Pinecone: $70

Average Query Latency (P99)
type: PropertyValue
value: Chroma: N/A | Pinecone: 50-100ms

Setup to Production Time
type: PropertyValue
value: Chroma: N/A | Pinecone: 0.5

Starting Monthly Cost
type: PropertyValue
value: Chroma: N/A | Pinecone: $10 minimum

Maximum Query Throughput
type: PropertyValue
value: Chroma: N/A | Pinecone: 5,000,000+

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

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

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

Monthly Cost (1M vectors, 768 dims)
type: PropertyValue
value: Chroma: N/A | Pinecone: $4.00 + query fees

Time to Production
type: PropertyValue
value: Chroma: N/A | Pinecone: 15-30 minutes

Hybrid Search Support
type: PropertyValue
value: Chroma: N/A | Pinecone: Yes (dense + BM25)

API Compatibility
type: PropertyValue
value: Chroma: N/A | Pinecone: Proprietary SDK + REST

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

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

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

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

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

SLA Uptime Guarantee
type: PropertyValue
value: Chroma: N/A | Pinecone: 99.99%

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

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

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

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

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

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

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

Time to First Production Query
type: PropertyValue
value: Chroma: N/A | Pinecone: ~15 minutes

Cost for 1M Daily Queries + 100GB Storage/Month
type: PropertyValue
value: Chroma: N/A | Pinecone: $500-800

Maximum Vector Dimension Support
type: PropertyValue
value: Chroma: N/A | Pinecone: 20,000 dimensions

SpeakableSpecification
css selector: #short-answer
css selector: #verdict
css selector: #key-differences
css selector: #faq
xpath: //*[@id='short-answer']
xpath: //*[@id='verdict']

Chroma — Wikipedia
type: CreativeWork

Pinecone — Wikipedia
type: CreativeWork

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

Hybrid Search (Vector + Keyword)
type: PropertyValue
value reference: Features

Multi-Modal Support
type: PropertyValue
value reference: Features

Enterprise Features (RBAC/Multi-tenancy)
type: PropertyValue
value reference: Features

GitHub Stars
type: PropertyValue
value reference: Adoption & Community

Deployment Options
type: PropertyValue
value reference: Infrastructure

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

Supported Data Sources
type: PropertyValue
value reference: Integration

Query Latency (P95)
type: PropertyValue
value reference: Performance

Maximum Embeddings
type: PropertyValue
value reference: Scalability

LLM Integration
type: PropertyValue
value reference: Features

Learning Curve (Hours)
type: PropertyValue
value reference: Ease of Use

Production Deployments Reported
type: PropertyValue
value reference: Adoption

Deployment Complexity
type: PropertyValue
value reference: Operations

Initial Setup Time
type: PropertyValue
value reference: User Experience

Minimum Monthly Cost
type: PropertyValue
value reference: Pricing

Production Plan Cost
type: PropertyValue
value reference: Pricing

Maximum Vector Capacity
type: PropertyValue
value reference: Performance & Scale

Query Latency (p99) at 100M Vectors
type: PropertyValue
value reference: Performance

REST API Support
type: PropertyValue
value reference: Integration

RBAC & Enterprise Security
type: PropertyValue
value reference: Security

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

Single-Vector Search Latency (1M vectors)
type: PropertyValue
value reference: Performance

Maximum Supported Vector Dimensions
type: PropertyValue
value reference: Capability

Native SQL Support
type: PropertyValue
value reference: Querying

Embedding Auto-Generation
type: PropertyValue
value reference: Feature

Open Source Availability
type: PropertyValue
value reference: Deployment

Managed Cloud Cost (1M queries/month)
type: PropertyValue
value reference: Pricing

Relational Data Integration
type: PropertyValue
value reference: Capability

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

Maximum Recommended Vectors
type: PropertyValue
value reference: Scalability

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

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

Maximum Recommended Vector Count
type: PropertyValue
value reference: Scalability

Minimum RAM Requirement (Single Node)
type: PropertyValue
value reference: Infrastructure

Advanced Filtering Support
type: PropertyValue
value reference: Query Capabilities

Multi-Tenancy
type: PropertyValue
value reference: Enterprise Features

Open Source License
type: PropertyValue
value reference: Licensing

Enterprise Support SLA
type: PropertyValue
value reference: Support

Setup Time (minutes to first working example)
type: PropertyValue
value reference: Developer Experience

Maximum Vector Capacity (single instance)
type: PropertyValue
value reference: Scalability

Query Latency at 1M vectors
type: PropertyValue
value reference: Performance

Memory per Million Vectors
type: PropertyValue
value reference: Resource Usage

Built-in Embedding Model Support
type: PropertyValue
value reference: Features

Index Type Options
type: PropertyValue
value reference: Flexibility

GPU Acceleration Support
type: PropertyValue
value reference: Hardware Optimization

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

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

Metadata Filtering Complexity
type: PropertyValue
value reference: Features

Supported Programming Languages
type: PropertyValue
value reference: Compatibility

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

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

Maximum Vector Dimensions
type: PropertyValue
value reference: Capability

SQL Query Support
type: PropertyValue
value reference: Capability

GitHub Stars (2026)
type: PropertyValue
value reference: Community

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

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

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

Initial Cost
type: PropertyValue
value reference: Pricing

Monthly Cost at 100M Vectors
type: PropertyValue
value reference: Pricing

Vector Store Integrations
type: PropertyValue
value reference: RAG Support

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

Free Tier Vector Capacity
type: PropertyValue
value reference: Limits

Pricing Model
type: PropertyValue
value reference: Cost & Licensing

Estimated Monthly Cost at 100GB
type: PropertyValue
value reference: Cost & Business

Vector Dimension Limit
type: PropertyValue
value reference: Performance & Scalability

GitHub Stars/Community Size
type: PropertyValue
value reference: Community & Adoption

Self-Hosting Available
type: PropertyValue
value reference: Deployment

Cost for 1M Monthly Read Operations
type: PropertyValue
value reference: Pricing

Vector Dimensionality Support
type: PropertyValue
value reference: Features

Uptime SLA Guarantee
type: PropertyValue
value reference: Reliability

SQL Relational Query Integration
type: PropertyValue
value reference: Features

GitHub Community Stars
type: PropertyValue
value reference: Community

Free Tier Vector Limit
type: PropertyValue
value reference: Pricing & Limits

Estimated Monthly Cost (1M vectors)
type: PropertyValue
value reference: Pricing & Limits

Native Hybrid Search Support
type: PropertyValue
value reference: Features

Monthly Cost (1M vectors, 1K queries/day)
type: PropertyValue
value reference: Pricing

Maximum Vectors Supported
type: PropertyValue
value reference: Scalability

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

Setup Time (production-ready)
type: PropertyValue
value reference: Ease of Use

Native Integration Count
type: PropertyValue
value reference: Features

Data Export Capability
type: PropertyValue
value reference: Flexibility

Free Tier Capacity
type: PropertyValue
value reference: Limits

Production Starter Cost
type: PropertyValue
value reference: Pricing

Average Query Latency (P99)
type: PropertyValue
value reference: Performance

Setup to Production Time
type: PropertyValue
value reference: Operations

Starting Monthly Cost
type: PropertyValue
value reference: Pricing

Maximum Query Throughput
type: PropertyValue
value reference: Performance

P99 Query Latency
type: PropertyValue
value reference: Performance

Code Customization
type: PropertyValue
value reference: Flexibility

Free Tier Availability
type: PropertyValue
value reference: Pricing

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

Time to Production
type: PropertyValue
value reference: Deployment

Hybrid Search Support
type: PropertyValue
value reference: Features

API Compatibility
type: PropertyValue
value reference: Integration

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

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

Supported Indexing Algorithms
type: PropertyValue
value reference: Capability

Infrastructure Required
type: PropertyValue
value reference: Operations

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