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Comparison

langflow vs kitaru

Verdict

Pick langflow when license: langflow is MIT, kitaru is Apache-2.0; pick kitaru when license: kitaru is Apache-2.0, langflow is MIT.

Markdown twin · langflow alternatives · kitaru alternatives

GraphCanon updated today

langflow logo

langflow

langflow-ai/langflow

★ 152kpushed Jul 11, 2026
vs
kitaru logo

kitaru

zenml-io/kitaru

★ 202pushed Jul 10, 2026

Trust & integrity

Signallangflowkitaru
Maintenance
Very active (0d since push)
As of today · github_public_v1
Very active (1d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
No criticals
As of today · osv@v1
No criticals
As of today · mcp_manifest@v1
langflow trust reportkitaru trust reportTrust methodology

Tagline

langflow
Langflow is a powerful tool for building and deploying AI-powered agents and workflows.
kitaru
Record, replay, and improve AI agents in production, built on ZenML

Stars

langflow
152k
kitaru
202

Forks

langflow
9.7k
kitaru
15

Open issues

langflow
975
kitaru
36

Language

langflow
Python
kitaru
Python

Adopt for

langflow
Langflow specializes in creating and deploying AI agents and complex workflows through a versatile GUI-based approach.
kitaru
-

Persona

langflow
-
kitaru
-

Runtime

langflow
-
kitaru
-

License

langflow
MIT
kitaru
Apache-2.0

Last pushed

langflow
Jul 11, 2026
kitaru
Jul 10, 2026

Categories

langflow
AI Agents, Inference & Serving
kitaru
AI Agents, Inference & Serving, LLM Frameworks

Trust and health

Days since push

langflow
0d
kitaru
1d

Open issues (now)

langflow
975
kitaru
36

Full report

langflow
Trust report
kitaru
Trust report

Shared compatibility

  • Python · langflow: Python runtime · kitaru: Python runtime

Choose langflow if…

  • License: langflow is MIT, kitaru is Apache-2.0.
  • Tags unique to langflow: agents, chatgpt, generative-ai, large-language-models.
  • - When you need an intuitive graphical interface to manage the creation of AI agents and workflows without deep coding knowledge.

When NOT to use langflow

  • - For developers preferring a code-first approach who find GUI interfaces restrictive for customization and workflow.
  • - When the project does not align with or leverage the specific topics of focus such as ChatGPT, multi-agent systems, or requires integration with platforms that Langflow's graphical interface cannot旖
GitHubDetails

Choose kitaru if…

  • License: kitaru is Apache-2.0, langflow is MIT.
  • Tags unique to kitaru: agent-framework, ai-agents, checkpoints, durable-execution.
  • Also covers LLM Frameworks.

When NOT to use kitaru

  • 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.
GitHubDetails

Explore

langflow trust report →kitaru trust report →AI Agents category →Inference & Serving category →LLM Frameworks category →All comparisonsStack workflowsTrending tools

Sources

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

GitHub stars on cards: langflow 152k · kitaru 202 (synced Jul 11, 2026).

Common questions

What is the difference between langflow and kitaru?
langflow: Langflow is a powerful tool for building and deploying AI-powered agents and workflows.. kitaru: Record, replay, and improve AI agents in production, built on ZenML. See the comparison table for live GitHub stats and shared categories.
When should I choose langflow over kitaru?
Choose langflow over kitaru when License: langflow is MIT, kitaru is Apache-2.0; Tags unique to langflow: agents, chatgpt, generative-ai, large-language-models; - When you need an intuitive graphical interface to manage the creation of AI agents and workflows without deep coding knowledge.
When should I choose kitaru over langflow?
Choose kitaru over langflow when License: kitaru is Apache-2.0, langflow is MIT; Tags unique to kitaru: agent-framework, ai-agents, checkpoints, durable-execution; Also covers LLM Frameworks.
When should I avoid langflow?
- For developers preferring a code-first approach who find GUI interfaces restrictive for customization and workflow. - When the project does not align with or leverage the specific topics of focus such as ChatGPT, multi-agent systems, or requires integration with platforms that Langflow's graphical interface cannot旖
When should I avoid kitaru?
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.
Is langflow or kitaru more popular on GitHub?
langflow has more GitHub stars (151,697 vs 202). Stars measure visibility, not whether either tool fits your constraints.
Are langflow and kitaru open source?
Yes - both are open-source projects on GitHub (langflow: MIT, kitaru: Apache-2.0).
Where can I find alternatives to langflow or kitaru?
GraphCanon lists graph-backed alternatives at langflow alternatives and kitaru alternatives (langflow markdown twin, kitaru 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, langflow or kitaru?
langflow: Very active. kitaru: 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 langflow and kitaru?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: langflow trust report; kitaru trust report.