Home/Compare/koog vs langchain

Comparison

koog vs langchain

Verdict

Pick koog when koog is primarily Kotlin; langchain is Python; pick langchain when langchain is primarily Python; koog is Kotlin.

Markdown twin · koog alternatives · langchain alternatives

GraphCanon updated today

koog logo

koog

JetBrains/koog

4.4kpushed Jul 6, 2026
vs
langchain logo

langchain

langchain-ai/langchain

142kpushed Jul 14, 2026

Trust & integrity

Signalkooglangchain
Maintenance
Active (9d since push)
As of today · github_public_v1
Very active (0d since push)
As of 1d · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Organization account
As of 1d · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of today · osv@v1
No lockfile (source not queried)
As of 4d · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1

Tagline

koog
Koog is a JVM (Java and Kotlin) framework for building predictable, fault-tolerant and enterprise-ready AI agents across all platforms – from backend services to Android and iOS, JVM, and even in-brow
langchain
The agent engineering platform.

Stars

koog
4.4k
langchain
142k

Forks

koog
447
langchain
24k

Open issues

koog
162
langchain
419

Language

koog
Kotlin
langchain
Python

Adopt for

koog
-
langchain
LangChain is an open-source platform designed specifically for building agents and applications that leverage large language models (LLMs). It provides a standard framework to develop interoperable components and connect

Persona

koog
-
langchain
-

Runtime

koog
-
langchain
-

License

koog
Apache-2.0
langchain
MIT License, allowing free use for both personal and commercial purposes under its stipulated terms.

Last pushed

koog
Jul 6, 2026
langchain
Jul 14, 2026

Categories

koog
AI Agents, Inference & Serving, LLM Frameworks
langchain
AI Agents, LLM Frameworks

Trust and health

Maintenance

koog
Active (82%)
langchain
Very active (96%)

Days since push

koog
9d
langchain
0d

Open issues (now)

koog
162
langchain
419

Full report

langchain
Trust report

Choose koog if…

  • koog is primarily Kotlin; langchain is Python.
  • License: koog is Apache-2.0, langchain is MIT.
  • Tags unique to koog: agentframework, agentic-ai, ai, ai-agents-framework.
  • Also covers Inference & Serving.

When NOT to use koog

  • AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

Choose langchain if…

  • langchain is primarily Python; koog is Kotlin.
  • License: langchain is MIT, koog is Apache-2.0.
  • Pricing: LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI..
  • Tags unique to langchain: ai-agents, chatgpt, deepagents, enterprise.
  • * When aiming to build complex AI-powered agents or applications requiring high-level capabilities like planning, subagent interaction, and file system operations.

When NOT to use langchain

  • * When working on smaller, less complex projects where full-scale integration with sophisticated components is not necessary as LangChain's extensive features might introduce unnecessary complexity.
  • * If you are primarily focused on JavaScript or TypeScript development as the primary focus of LangChain is Python. Although there is a JS/TS equivalent (LangChain.js), it may not offer the same depth
  • * For projects requiring heavy customization at lower levels, where a more granular control over individual components is required rather than working with an integrated framework.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: koog 4.4k · langchain 142k (synced Jul 15, 2026).

Common questions

What is the difference between koog and langchain?
koog: Koog is a JVM (Java and Kotlin) framework for building predictable, fault-tolerant and enterprise-ready AI agents across all platforms – from backend services to Android and iOS, JVM, and even in-brow. langchain: The agent engineering platform.. See the comparison table for live GitHub stats and shared categories.
When should I choose koog over langchain?
Choose koog over langchain when koog is primarily Kotlin; langchain is Python; License: koog is Apache-2.0, langchain is MIT; Tags unique to koog: agentframework, agentic-ai, ai, ai-agents-framework; Also covers Inference & Serving.
When should I choose langchain over koog?
Choose langchain over koog when langchain is primarily Python; koog is Kotlin; License: langchain is MIT, koog is Apache-2.0; Pricing: LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI.; Tags unique to langchain: ai-agents, chatgpt, deepagents, enterprise; * When aiming to build complex AI-powered agents or applications requiring high-level capabilities like planning, subagent interaction, and file system operations.
When should I avoid koog?
AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
When should I avoid langchain?
* When working on smaller, less complex projects where full-scale integration with sophisticated components is not necessary as LangChain's extensive features might introduce unnecessary complexity. * If you are primarily focused on JavaScript or TypeScript development as the primary focus of LangChain is Python. Although there is a JS/TS equivalent (LangChain.js), it may not offer the same depth * For projects requiring heavy customization at lower levels, where a more granular control over individual components is required rather than working with an integrated framework.
Is koog or langchain more popular on GitHub?
langchain has more GitHub stars (141,713 vs 4,447). Stars measure visibility, not whether either tool fits your constraints.
Are koog and langchain open source?
Yes - both are open-source projects on GitHub (koog: Apache-2.0, langchain: MIT).
Where can I find alternatives to koog or langchain?
GraphCanon lists graph-backed alternatives at koog alternatives and langchain alternatives (koog markdown twin, langchain markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, koog or langchain?
koog: Active. langchain: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for koog and langchain?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: koog trust report; langchain trust report.

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