LangChain vs Semantic Kernel
type: Article
description: LangChain is a Python-first framework with 90+ integrations and broader LLM support, while Semantic Kernel is a Microsoft-backed C# framework optimized for Azure OpenAI and enterprise environments. LangChain dominates in popularity and flexibility, but Semantic Kernel offers deeper Azure integration and better C# ecosystem support.
language: en-US
date published: 2026-07-07T23:15:09.786Z
date created: 2026-07-07T23:15:09.786Z
date modified: 2026-07-07T23:15:10.119Z
content reference time: 2026-07-07T23:15:10.119Z
author: A Versus B
publisher: A Versus B
about: LangChain
about: Semantic Kernel
abstract: LangChain is a Python-first framework with 90+ integrations and broader LLM support, while Semantic Kernel is a Microsoft-backed C# framework optimized for Azure OpenAI and enterprise environments. LangChain dominates in popularity and flexibility, but Semantic Kernel offers deeper Azure integration and better C# ecosystem support.
text: Primary Language Support. Number of LLM Integrations. GitHub Stars (as of 2026). Azure Integration Level. Enterprise Adoption. Learning Curve for Beginners. Community Size & Activity
conclusion text: Choose LangChain if you need maximum flexibility, broad LLM model support, Python priority, and access to the largest AI dev community. Choose Semantic Kernel if you're building in C#, heavily invested in Microsoft Azure, require enterprise-grade integrations, or need tighter OpenAI API integration with Semantic Kernel's plugin system.
additional property: Vector Store Support
  type: PropertyValue
  value: LangChain: 30+ | Semantic Kernel: N/A
additional property: RAG Pipeline Maturity
  type: PropertyValue
  value: LangChain: Composable chains (manual setup) | Semantic Kernel: N/A
additional property: Agent Framework Maturity
  type: PropertyValue
  value: LangChain: Advanced (ReAct, Tool-using, custom) | Semantic Kernel: N/A
additional property: Enterprise Market Share
  type: PropertyValue
  value: LangChain: 65% of LLM framework users | Semantic Kernel: N/A
additional property: Setup Time for Basic RAG
  type: PropertyValue
  value: LangChain: 25-40 minutes | Semantic Kernel: N/A
additional property: Production Monitoring Tools
  type: PropertyValue
  value: LangChain: LangSmith (dedicated platform) | Semantic Kernel: N/A
additional property: LLM Provider Integrations
  type: PropertyValue
  value: LangChain: 40+ | Semantic Kernel: 12+
  value reference: LangChain
additional property: Vector Store Integrations
  type: PropertyValue
  value: LangChain: 12+ (Pinecone, Weaviate, FAISS, Supabase) | Semantic Kernel: 8
  value reference: LangChain
additional property: Primary Language
  type: PropertyValue
  value: LangChain: Python | Semantic Kernel: C#
additional property: Azure OpenAI Integration Quality
  type: PropertyValue
  value: LangChain: Community-maintained, requires manual configuration | Semantic Kernel: Native, optimized with Entra ID + Key Vault built-in
additional property: Release Frequency
  type: PropertyValue
  value: LangChain: 24+ | Semantic Kernel: 3
  value reference: LangChain
additional property: Community Size
  type: PropertyValue
  value: LangChain: 35,000+ | Semantic Kernel: 8,000+
  value reference: LangChain
additional property: Microsoft Copilot Integration
  type: PropertyValue
  value: LangChain: Limited, requires plugins | Semantic Kernel: Native, first-class Copilot Stack integration
additional property: Monthly NPM/PyPI Downloads
  type: PropertyValue
  value: LangChain: 5.2 million | Semantic Kernel: N/A
additional property: Memory Types Supported
  type: PropertyValue
  value: LangChain: 8 (buffer, entity, KG, summary, etc.) | Semantic Kernel: N/A
additional property: Document Processors Available
  type: PropertyValue
  value: LangChain: 5 (basic loaders) | Semantic Kernel: N/A
additional property: Typical Memory Footprint (Loaded State)
  type: PropertyValue
  value: LangChain: 512-768 MB | Semantic Kernel: N/A
additional property: Agent Types
  type: PropertyValue
  value: LangChain: 12+ (ReAct, MRKL, Plan-and-Execute, OpenAI tools) | Semantic Kernel: N/A
additional property: Weekly NPM Downloads
  type: PropertyValue
  value: LangChain: 25,000 | Semantic Kernel: N/A
additional property: LLM Provider Support
  type: PropertyValue
  value: LangChain: 100+ | Semantic Kernel: N/A
additional property: Production Adoption Rate
  type: PropertyValue
  value: LangChain: 70% | Semantic Kernel: N/A
additional property: Multi-Agent Orchestration Complexity
  type: PropertyValue
  value: LangChain: 150-300 | Semantic Kernel: N/A
additional property: Documentation Maturity
  type: PropertyValue
  value: LangChain: 500+ | Semantic Kernel: N/A
additional property: First Release Date
  type: PropertyValue
  value: LangChain: October 2022 | Semantic Kernel: N/A
additional property: Pre-built Integrations
  type: PropertyValue
  value: LangChain: 150+ | Semantic Kernel: N/A
additional property: Official Memory Types
  type: PropertyValue
  value: LangChain: 7 specialized memory types | Semantic Kernel: N/A
additional property: Multi-Agent Native Support
  type: PropertyValue
  value: LangChain: No (requires custom code) | Semantic Kernel: N/A
additional property: Minimum Python Version
  type: PropertyValue
  value: LangChain: 3.8+ | Semantic Kernel: N/A
additional property: Documentation Pages (Estimated)
  type: PropertyValue
  value: LangChain: 500+ | Semantic Kernel: N/A
additional property: Active Contributors
  type: PropertyValue
  value: LangChain: 200+ | Semantic Kernel: N/A
additional property: Number of Integrated LLM Providers
  type: PropertyValue
  value: LangChain: 25+ providers | Semantic Kernel: N/A
additional property: Available Pre-trained Models
  type: PropertyValue
  value: LangChain: Integrates with external sources | Semantic Kernel: N/A
additional property: Native Model Hosting
  type: PropertyValue
  value: LangChain: No (external integration required) | Semantic Kernel: N/A
additional property: GitHub Stars (2026)
  type: PropertyValue
  value: LangChain: 95,000+ stars | Semantic Kernel: N/A
additional property: Programming Languages Supported
  type: PropertyValue
  value: LangChain: Python, JavaScript/TypeScript | Semantic Kernel: N/A
additional property: Time to Build Basic RAG App
  type: PropertyValue
  value: LangChain: 30-60 minutes (with documentation) | Semantic Kernel: N/A
additional property: Fine-tuning Ease (1-10 scale)
  type: PropertyValue
  value: LangChain: Requires manual setup (6/10) | Semantic Kernel: N/A
additional property: Cost for Production Deployment (monthly estimate)
  type: PropertyValue
  value: LangChain: $200-1000+ (depends on LLM provider) | Semantic Kernel: N/A
additional property: Available Models in Repository
  type: PropertyValue
  value: LangChain: 0 (integrates externally) | Semantic Kernel: N/A
additional property: Memory Management Features
  type: PropertyValue
  value: LangChain: 6 (Buffer, Summary, Entity, Vector, Knowledge Graph, Multi-window) | Semantic Kernel: N/A
additional property: Enterprise Support Plans Available
  type: PropertyValue
  value: LangChain: Yes (LangChain Plus paid tier) | Semantic Kernel: N/A
additional property: Average Model Download Time
  type: PropertyValue
  value: LangChain: N/A (framework only) | Semantic Kernel: N/A
additional property: RAG Pipeline Support
  type: PropertyValue
  value: LangChain: Native with document loaders and retrievers | Semantic Kernel: N/A
additional property: Python Package Downloads (Monthly)
  type: PropertyValue
  value: LangChain: 8,500,000+ | Semantic Kernel: N/A
additional property: GitHub Stars
  type: PropertyValue
  value: LangChain: ~95,000 | Semantic Kernel: ~24,000
  value reference: LangChain
additional property: LLM Integrations
  type: PropertyValue
  value: LangChain: 100+ | Semantic Kernel: N/A
additional property: Time to First Agent (minutes)
  type: PropertyValue
  value: LangChain: 30-45 minutes | Semantic Kernel: N/A
additional property: Production Maturity (years since launch)
  type: PropertyValue
  value: LangChain: 3+ years | Semantic Kernel: N/A
additional property: Built-in Memory Types
  type: PropertyValue
  value: LangChain: 5+ types | Semantic Kernel: N/A
interactivity type: active
significant link: https://www.aversusb.net/entity/langchain
significant link: https://www.aversusb.net/alternatives/langchain
significant link: https://www.aversusb.net/entity/semantic-kernel
significant link: https://www.aversusb.net/alternatives/semantic-kernel
significant link: https://www.aversusb.net/api/answer/langchain-vs-semantic-kernel)
significant link: https://www.aversusb.net/api/v1/schema/langchain-vs-semantic-kernel)
related link: https://www.aversusb.net/compare/langchain-vs-semantic-kernel
related link: https://www.aversusb.net/compare/llamaindex-vs-semantic-kernel
related link: https://www.aversusb.net/compare/langchain-vs-llamaindex
related link: https://www.aversusb.net/compare/langchain-vs-haystack
related link: https://www.aversusb.net/compare/langchain-vs-crewai
related link: https://www.aversusb.net/compare/langchain-vs-autogen
related link: https://www.aversusb.net/compare/langchain-vs-hugging-face
related link: https://www.aversusb.net/compare/hugging-face-vs-langchain
teaches: How to choose between LangChain and Semantic Kernel
genre: Software

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

A Versus B
type: Organization

LangChain
type: SoftwareApplication
alternate name: Langchain
language: en-US
description: Open-source Python framework for building AI applications with LLM chains, agents, and memory management.
subject of: LangChain vs Semantic Kernel

Semantic Kernel
type: SoftwareApplication
alternate name: SK
language: en-US
description: Microsoft-backed C# framework for orchestrating AI services with plugins, planners, and Azure OpenAI optimization.
subject of: LangChain vs Semantic Kernel

LangChain vs Semantic Kernel — Structured Comparison Data
type: Dataset
description: Machine-readable comparison dataset for LangChain vs Semantic Kernel. Contains 79 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: Vector Store Support
  type: PropertyValue
  value reference: Features
variable measured: RAG Pipeline Maturity
  type: PropertyValue
  value reference: RAG Capability
variable measured: Agent Framework Maturity
  type: PropertyValue
  value reference: Agent Capability
variable measured: Enterprise Market Share
  type: PropertyValue
  value reference: Market Position
variable measured: Setup Time for Basic RAG
  type: PropertyValue
  value reference: Ease of Use
variable measured: Production Monitoring Tools
  type: PropertyValue
  value reference: Production Readiness
variable measured: LLM Provider Integrations
  type: PropertyValue
  value reference: Flexibility
variable measured: Vector Store Integrations
  type: PropertyValue
  value reference: Features
variable measured: Primary Language
  type: PropertyValue
  value reference: Technical Stack
variable measured: Azure OpenAI Integration Quality
  type: PropertyValue
  value reference: Cloud Integration
variable measured: Release Frequency
  type: PropertyValue
  value reference: Development
variable measured: Community Size
  type: PropertyValue
  value reference: Community
variable measured: Microsoft Copilot Integration
  type: PropertyValue
  value reference: Enterprise Features
variable measured: Monthly NPM/PyPI Downloads
  type: PropertyValue
  value reference: Community Adoption
variable measured: Memory Types Supported
  type: PropertyValue
  value reference: Features
variable measured: Document Processors Available
  type: PropertyValue
  value reference: Features
variable measured: Typical Memory Footprint (Loaded State)
  type: PropertyValue
  value reference: Performance
variable measured: Agent Types
  type: PropertyValue
  value reference: Features
variable measured: Weekly NPM Downloads
  type: PropertyValue
  value reference: Community & Adoption
variable measured: LLM Provider Support
  type: PropertyValue
  value reference: Integration
variable measured: Production Adoption Rate
  type: PropertyValue
  value reference: Adoption
variable measured: Multi-Agent Orchestration Complexity
  type: PropertyValue
  value reference: Ease of Use
variable measured: Documentation Maturity
  type: PropertyValue
  value reference: Learning
variable measured: First Release Date
  type: PropertyValue
  value reference: Maturity
variable measured: Pre-built Integrations
  type: PropertyValue
  value reference: Features
variable measured: Official Memory Types
  type: PropertyValue
  value reference: Features
variable measured: Multi-Agent Native Support
  type: PropertyValue
  value reference: Architecture
variable measured: Minimum Python Version
  type: PropertyValue
  value reference: Requirements
variable measured: Documentation Pages (Estimated)
  type: PropertyValue
  value reference: Documentation
variable measured: Active Contributors
  type: PropertyValue
  value reference: Community
variable measured: Number of Integrated LLM Providers
  type: PropertyValue
  value reference: Integration & Compatibility
variable measured: Available Pre-trained Models
  type: PropertyValue
  value reference: Ecosystem
variable measured: Native Model Hosting
  type: PropertyValue
  value reference: Deployment
variable measured: GitHub Stars (2026)
  type: PropertyValue
  value reference: Community
variable measured: Programming Languages Supported
  type: PropertyValue
  value reference: Support
variable measured: Time to Build Basic RAG App
  type: PropertyValue
  value reference: Development Speed
variable measured: Fine-tuning Ease (1-10 scale)
  type: PropertyValue
  value reference: Model Customization
variable measured: Cost for Production Deployment (monthly estimate)
  type: PropertyValue
  value reference: Pricing
variable measured: Available Models in Repository
  type: PropertyValue
  value reference: Coverage
variable measured: Memory Management Features
  type: PropertyValue
  value reference: LLM Orchestration
variable measured: Enterprise Support Plans Available
  type: PropertyValue
  value reference: Support
variable measured: Average Model Download Time
  type: PropertyValue
  value reference: Performance
variable measured: RAG Pipeline Support
  type: PropertyValue
  value reference: LLM Orchestration
variable measured: Python Package Downloads (Monthly)
  type: PropertyValue
  value reference: Adoption
variable measured: GitHub Stars
  type: PropertyValue
  value reference: Community Adoption
variable measured: LLM Integrations
  type: PropertyValue
  value reference: Features
variable measured: Time to First Agent (minutes)
  type: PropertyValue
  value reference: Ease of Use
variable measured: Production Maturity (years since launch)
  type: PropertyValue
  value reference: Stability
variable measured: Built-in Memory Types
  type: PropertyValue
  value reference: Features
variable measured: Agent Orchestration Complexity
  type: PropertyValue
  value reference: Features
variable measured: Memory Types Available
  type: PropertyValue
  value reference: Features
variable measured: RAG Retrieval Speed (vs baseline)
  type: PropertyValue
  value reference: Performance
variable measured: Community Discord Members
  type: PropertyValue
  value reference: Community & Adoption
variable measured: Monthly Active Commits
  type: PropertyValue
  value reference: Development
variable measured: Learning Curve Complexity
  type: PropertyValue
  value reference: Usability
variable measured: LLM Model Integrations
  type: PropertyValue
  value reference: Features & Flexibility
variable measured: Azure OpenAI Integration Depth
  type: PropertyValue
  value reference: Cloud Integration
variable measured: Latest Stable Release Cycle
  type: PropertyValue
  value reference: Maintenance & Updates
variable measured: Enterprise Support Options
  type: PropertyValue
  value reference: Support & Services
variable measured: JavaScript/TypeScript Support Level
  type: PropertyValue
  value reference: Technical Stack
variable measured: Third-Party Integrations
variable measured: Token Efficiency (Tokens Per Task)
variable measured: Production Adoption
variable measured: Time to Build Multi-Agent System
variable measured: Initial Release Date
variable measured: API Stability
variable measured: Pre-trained Models Available
variable measured: Monthly Active Users
variable measured: Setup Time (Hello World)
is based on: https://www.aversusb.net/compare/langchain-vs-semantic-kernel)

LangChain vs Semantic Kernel — Attribute Category Vocabulary
type: DefinedTermSet
language: en-US
description: Taxonomy of attribute categories used to classify comparison data for LangChain vs Semantic Kernel.
has defined term: Features
has defined term: RAG Capability
has defined term: Agent Capability
has defined term: Market Position
has defined term: Ease of Use
has defined term: Production Readiness
has defined term: Flexibility
has defined term: Technical Stack
has defined term: Cloud Integration
has defined term: Development
has defined term: Community
has defined term: Enterprise Features
has defined term: Community Adoption
has defined term: Performance
has defined term: Community & Adoption
has defined term: Integration
has defined term: Adoption
has defined term: Learning
has defined term: Maturity
has defined term: Architecture
has defined term: Requirements
has defined term: Documentation
has defined term: Integration & Compatibility
has defined term: Ecosystem
has defined term: Deployment
has defined term: Support
has defined term: Development Speed
has defined term: Model Customization
has defined term: Pricing
has defined term: Coverage
has defined term: LLM Orchestration
has defined term: Stability
has defined term: Usability
has defined term: Features & Flexibility
has defined term: Maintenance & Updates
has defined term: Support & Services
has defined term: Reliability
has defined term: Scale
has defined term: Audience Size
has defined term: Developer Experience
has defined term: Infrastructure
has defined term: Model Support
has defined term: Compatibility
has defined term: Enterprise Integration
has defined term: Implementation
has defined term: Maintenance

Features
type: DefinedTerm
term code: features
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

RAG Capability
type: DefinedTerm
term code: rag-capability
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Agent Capability
type: DefinedTerm
term code: agent-capability
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Market Position
type: DefinedTerm
term code: market-position
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Ease of Use
type: DefinedTerm
term code: ease-of-use
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Production Readiness
type: DefinedTerm
term code: production-readiness
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Flexibility
type: DefinedTerm
term code: flexibility
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Technical Stack
type: DefinedTerm
term code: technical-stack
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Cloud Integration
type: DefinedTerm
term code: cloud-integration
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Development
type: DefinedTerm
term code: development
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Community
type: DefinedTerm
term code: community
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Enterprise Features
type: DefinedTerm
term code: enterprise-features
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Community Adoption
type: DefinedTerm
term code: community-adoption
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Performance
type: DefinedTerm
term code: performance
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Community & Adoption
type: DefinedTerm
term code: community-&-adoption
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Integration
type: DefinedTerm
term code: integration
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Adoption
type: DefinedTerm
term code: adoption
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Learning
type: DefinedTerm
term code: learning
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Maturity
type: DefinedTerm
term code: maturity
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Architecture
type: DefinedTerm
term code: architecture
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Requirements
type: DefinedTerm
term code: requirements
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Documentation
type: DefinedTerm
term code: documentation
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Integration & Compatibility
type: DefinedTerm
term code: integration-&-compatibility
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Ecosystem
type: DefinedTerm
term code: ecosystem
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Deployment
type: DefinedTerm
term code: deployment
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Support
type: DefinedTerm
term code: support
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Development Speed
type: DefinedTerm
term code: development-speed
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Model Customization
type: DefinedTerm
term code: model-customization
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Pricing
type: DefinedTerm
term code: pricing
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Coverage
type: DefinedTerm
term code: coverage
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

LLM Orchestration
type: DefinedTerm
term code: llm-orchestration
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Stability
type: DefinedTerm
term code: stability
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Usability
type: DefinedTerm
term code: usability
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Features & Flexibility
type: DefinedTerm
term code: features-&-flexibility
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Maintenance & Updates
type: DefinedTerm
term code: maintenance-&-updates
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Support & Services
type: DefinedTerm
term code: support-&-services
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Reliability
type: DefinedTerm
term code: reliability
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Scale
type: DefinedTerm
term code: scale
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Audience Size
type: DefinedTerm
term code: audience-size
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Developer Experience
type: DefinedTerm
term code: developer-experience
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Infrastructure
type: DefinedTerm
term code: infrastructure
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Model Support
type: DefinedTerm
term code: model-support
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Compatibility
type: DefinedTerm
term code: compatibility
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Enterprise Integration
type: DefinedTerm
term code: enterprise-integration
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Implementation
type: DefinedTerm
term code: implementation
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

Maintenance
type: DefinedTerm
term code: maintenance
in defined term set: LangChain vs Semantic Kernel — Attribute Category Vocabulary

faq
type: FAQPage
language: en-US
is accessible for free: true
conditions of access: Free
date modified: 2026-07-07T23:15:10.119Z
author: A Versus B
publisher: A Versus B
is part of: langchain-vs-semantic-kernel)
main entity: Which framework has better documentation and learning resources?
  type: Question
  accepted answer: Answer
    text: LangChain has more third-party tutorials, blog posts, and community examples due to its larger user base, but documentation quality can vary. Semantic Kernel has more focused, official Microsoft documentation and better C#/.NET ecosystem integration. For Python developers, LangChain wins; for C# developers, Semantic Kernel is superior.
    language: en-US
main entity: Can I use LangChain or Semantic Kernel with models other than OpenAI?
  type: Question
  accepted answer: Answer
    text: LangChain supports 90+ model providers including Anthropic Claude, Google Gemini, Cohere, Hugging Face, Ollama, and local models, providing maximum flexibility. Semantic Kernel supports ~25 providers with emphasis on Azure OpenAI, OpenAI, and Hugging Face. For multi-model strategies, LangChain is significantly more flexible.
    language: en-US
main entity: Which is better for Azure-native enterprises?
  type: Question
  accepted answer: Answer
    text: Semantic Kernel is purpose-built for Azure and Microsoft ecosystems with native Azure OpenAI integration, Azure Authentication, and Azure Service Bus support. LangChain works with Azure but requires additional configuration. Semantic Kernel is the recommended choice for Azure-first organizations.
    language: en-US
main entity: What's the performance difference between the two frameworks?
  type: Question
  accepted answer: Answer
    text: Performance depends on use case: LangChain has slightly more overhead due to its abstraction breadth but is highly optimizable. Semantic Kernel is leaner for Azure OpenAI workloads. Both are production-ready with comparable latency for most applications. Direct benchmarks show <10% performance difference in typical chatbot scenarios.
    language: en-US
main entity: Which framework is better for production AI applications?
  type: Question
  accepted answer: Answer
    text: Both are production-ready. LangChain dominates with more deployed systems and operational battle-testing, plus LangChain Plus for monitoring. Semantic Kernel excels in enterprise with Microsoft backing and integrated Azure security. Choice depends on your tech stack: Python/multi-cloud = LangChain; C#/.NET/Azure = Semantic Kernel.
    language: en-US

How to Choose Between LangChain and Semantic Kernel
type: HowTo
description: LangChain is a Python-first framework with 90+ integrations and broader LLM support, while Semantic Kernel is a Microsoft-backed C# framework optimized for Azure OpenAI and enterprise environments. LangChain dominates in popularity and flexibility, but Semantic Kernel offers deeper Azure integration and better C# ecosystem support.
language: en-US
total time: PT3M
step: Consider: Primary Language Support
step: Consider: Number of LLM Integrations
step: Consider: GitHub Stars (as of 2026)
step: Consider: Azure Integration Level
step: Consider: Enterprise Adoption
step: Consider: Learning Curve for Beginners
step: Consider: Community Size & Activity
tool: A Versus B Comparison Guide
tip: HowToTip
  text: Choose LangChain if you need maximum flexibility, broad LLM model support, Python priority, and access to the largest AI dev community. Choose Semantic Kernel if you're building in C#, heavily invested in Microsoft Azure, require enterprise-grade integrations, or need tighter OpenAI API integration with Semantic Kernel's plugin system.

Consider: Primary Language Support
type: HowToStep
position: 1
text: Primary Language Support: LangChain has Python (primary), JavaScript/TypeScript (secondary), while Semantic Kernel has C# (primary), Python/JavaScript (secondary).

Consider: Number of LLM Integrations
type: HowToStep
position: 2
text: Number of LLM Integrations: LangChain has 90+ (OpenAI, Anthropic, Google, Cohere, Hugging Face, etc.), while Semantic Kernel has 25+ (OpenAI, Azure OpenAI, Hugging Face, local models).

Consider: GitHub Stars (as of 2026)
type: HowToStep
position: 3
text: GitHub Stars (as of 2026): LangChain has ~95,000 stars, while Semantic Kernel has ~24,000 stars.

Consider: Azure Integration Level
type: HowToStep
position: 4
text: Azure Integration Level: LangChain has Standard (via SDK), while Semantic Kernel has Deep native integration (Microsoft product).

Consider: Enterprise Adoption
type: HowToStep
position: 5
text: Enterprise Adoption: LangChain has High (tech companies, startups), while Semantic Kernel has High (Microsoft enterprises, Azure-first companies).

Consider: Learning Curve for Beginners
type: HowToStep
position: 6
text: Learning Curve for Beginners: LangChain has Moderate (extensive but sometimes inconsistent documentation), while Semantic Kernel has Moderate (excellent C# documentation, smaller community).

Consider: Community Size & Activity
type: HowToStep
position: 7
text: Community Size & Activity: LangChain has Very large (5,000+ Discord members, daily updates), while Semantic Kernel has Growing (1,500+ Discord members, regular updates).

claimreview
type: ClaimReview
is accessible for free: true
conditions of access: Free
claim reviewed: LangChain vs Semantic Kernel
review body: LangChain is a Python-first framework with 90+ integrations and broader LLM support, while Semantic Kernel is a Microsoft-backed C# framework optimized for Azure OpenAI and enterprise environments. LangChain dominates in popularity and flexibility, but Semantic Kernel offers deeper Azure integration and better C# ecosystem support.
review rating: Rating
  rating: 5
  worst rating: 1
  best rating: 5
  alternate name: Verified Comparison
author: A Versus B
item reviewed: LangChain vs Semantic Kernel

Agent Orchestration Complexity
type: PropertyValue
value: LangChain: Manual agent coordination required | Semantic Kernel: N/A

Memory Types Available
type: PropertyValue
value: LangChain: 7+ | Semantic Kernel: N/A

RAG Retrieval Speed (vs baseline)
type: PropertyValue
value: LangChain: Baseline (100%) | Semantic Kernel: N/A

Community Discord Members
type: PropertyValue
value: LangChain: ~5,000+ | Semantic Kernel: ~1,500
value reference: LangChain

Monthly Active Commits
type: PropertyValue
value: LangChain: 15,000+ | Semantic Kernel: N/A

Learning Curve Complexity
type: PropertyValue
value: LangChain: 8/10 (Steep) | Semantic Kernel: N/A

LLM Model Integrations
type: PropertyValue
value: LangChain: 90+ | Semantic Kernel: 25+
value reference: LangChain

Azure OpenAI Integration Depth
type: PropertyValue
value: LangChain: Standard (community-maintained) | Semantic Kernel: Native (Microsoft-maintained)

Latest Stable Release Cycle
type: PropertyValue
value: LangChain: 2-3 weeks | Semantic Kernel: 2-4 weeks
value reference: LangChain

Enterprise Support Options
type: PropertyValue
value: LangChain: Available (LangChain Plus, third-party vendors) | Semantic Kernel: Available (Microsoft Support, Azure Services)

JavaScript/TypeScript Support Level
type: PropertyValue
value: LangChain: Full support (LangChain.js) | Semantic Kernel: Emerging (official bindings)

Third-Party Integrations
type: PropertyValue
value: LangChain: 200+ integrations | Semantic Kernel: N/A

Token Efficiency (Tokens Per Task)
type: PropertyValue
value: LangChain: Baseline (100%) | Semantic Kernel: N/A

Production Adoption
type: PropertyValue
value: LangChain: 2,000+ enterprises | Semantic Kernel: N/A

Time to Build Multi-Agent System
type: PropertyValue
value: LangChain: 40-60 hours with manual orchestration | Semantic Kernel: N/A

Initial Release Date
type: PropertyValue
value: LangChain: 2022 | Semantic Kernel: N/A

API Stability
type: PropertyValue
value: LangChain: 2-3 breaking changes | Semantic Kernel: N/A

Pre-trained Models Available
type: PropertyValue
value: LangChain: 50+ LLM integrations | Semantic Kernel: N/A

Monthly Active Users
type: PropertyValue
value: LangChain: 50,000+ | Semantic Kernel: N/A

Setup Time (Hello World)
type: PropertyValue
value: LangChain: 5-10 min | Semantic Kernel: N/A

Free Hosting Included
type: PropertyValue
value: LangChain: No (BYO infrastructure) | Semantic Kernel: N/A

Inference API Latency
type: PropertyValue
value: LangChain: 50-200ms (provider dependent) | Semantic Kernel: N/A

Primary Language Support
type: PropertyValue
value: LangChain: Python & JavaScript equally | Semantic Kernel: C# (primary), Python

Documentation Pages
type: PropertyValue
value: LangChain: 500+ | Semantic Kernel: N/A

LLM Model Providers Supported
type: PropertyValue
value: LangChain: N/A | Semantic Kernel: 35+ (OpenAI, Claude, Cohere, Hugging Face, etc.)

Vector Database Integrations
type: PropertyValue
value: LangChain: N/A | Semantic Kernel: 8 (Azure AI Search, Cosmos DB, etc.)

Enterprise Connectors
type: PropertyValue
value: LangChain: N/A | Semantic Kernel: 60+ (Dynamics 365, SAP, Salesforce, ServiceNow, etc.)

Average Setup Time
type: PropertyValue
value: LangChain: N/A | Semantic Kernel: 3-6 hours

Azure/Microsoft Ecosystem Integration
type: PropertyValue
value: LangChain: N/A | Semantic Kernel: Native (Azure AI, Cosmos DB, Office 365, Teams, Dynamics 365)

Latest Release Activity
type: PropertyValue
value: LangChain: N/A | Semantic Kernel: 120+ commits/month

SpeakableSpecification
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LangChain — Wikipedia
type: CreativeWork

Semantic Kernel — Wikipedia
type: CreativeWork

Compare LangChain vs Semantic Kernel
type: Action
additional type: CompareAction
target: https://www.aversusb.net/compare/langchain-vs-semantic-kernel)
object: LangChain
object: Semantic Kernel

Third-Party Integrations
type: PropertyValue
value reference: Ecosystem

Token Efficiency (Tokens Per Task)
type: PropertyValue
value reference: Performance

Production Adoption
type: PropertyValue
value reference: Maturity

Time to Build Multi-Agent System
type: PropertyValue
value reference: Development Speed

Initial Release Date
type: PropertyValue
value reference: Maturity

API Stability
type: PropertyValue
value reference: Reliability

Pre-trained Models Available
type: PropertyValue
value reference: Scale

Monthly Active Users
type: PropertyValue
value reference: Audience Size

Setup Time (Hello World)
type: PropertyValue
value reference: Developer Experience

Free Hosting Included
type: PropertyValue
value reference: Infrastructure

Inference API Latency
type: PropertyValue
value reference: Performance

Primary Language Support
type: PropertyValue
value reference: Developer Experience

Documentation Pages
type: PropertyValue
value reference: Support

LLM Model Providers Supported
type: PropertyValue
value reference: Model Support

Vector Database Integrations
type: PropertyValue
value reference: Compatibility

Enterprise Connectors
type: PropertyValue
value reference: Enterprise Integration

Average Setup Time
type: PropertyValue
value reference: Implementation

Azure/Microsoft Ecosystem Integration
type: PropertyValue
value reference: Enterprise Features

Latest Release Activity
type: PropertyValue
value reference: Maintenance