--- title: "RagaAI-Catalyst vs kitaru" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/raga-ai-hub-ragaai-catalyst-vs-zenml-io-kitaru" tools: ["raga-ai-hub-ragaai-catalyst", "zenml-io-kitaru"] --- # RagaAI-Catalyst vs kitaru *GraphCanon updated Aug 20, 2026* ## Verdict Pick RagaAI-Catalyst if ragaAI-Catalyst emerges as a specialized Python framework designed for monitoring and evaluating AI agents, with unique features around self-hosted dashboards, advanced analytics, and support for tracing and debugging LL; pick kitaru if kitaru focuses on recording, replaying, and enhancing the performance of AI agents in production environments using technology from ZenML. [RagaAI-Catalyst](https://catalyst.raga.ai/) reports 16k GitHub stars, 3.6k forks, and 34 open issues, last pushed Feb 11, 2026. [kitaru](https://kitaru.ai) has 226 stars, 15 forks, and 49 open issues, last pushed Aug 3, 2026. Figures are from public GitHub metadata via [RagaAI-Catalyst's repository](https://github.com/raga-ai-hub/RagaAI-Catalyst) and [kitaru's repository](https://github.com/zenml-io/kitaru). | | [RagaAI-Catalyst](/tools/raga-ai-hub-ragaai-catalyst.md) | [kitaru](/tools/zenml-io-kitaru.md) | | --- | --- | --- | | Tagline | Python SDK for AI agent observability and evaluation | Record, replay, and improve AI agents in production, built on ZenML | | Stars | 16,148 | 226 | | Forks | 3,565 | 15 | | Open issues | 34 | 49 | | Language | Python | Python | | Adopt for | RagaAI-Catalyst emerges as a specialized Python framework designed for monitoring and evaluating AI agents, with unique features around self-hosted dashboards, advanced analytics, and support for tracing and debugging LL | Kitaru focuses on recording, replaying, and enhancing the performance of AI agents in production environments using technology from ZenML. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | AI Agents, Evaluation & Observability | AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [RagaAI-Catalyst](/tools/raga-ai-hub-ragaai-catalyst.md) | [kitaru](/tools/zenml-io-kitaru.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Very active (96%) | | Days since push | 189d | 0d | | Open issues (now) | 34 | 49 | | Stars delta | +5 (30d) | Unknown | | Open issues delta | 0 (30d) | Unknown | | Full report | [trust report](/tools/raga-ai-hub-ragaai-catalyst/trust.md) | [trust report](/tools/zenml-io-kitaru/trust.md) | ## Shared compatibility - **Python**: [RagaAI-Catalyst](/tools/raga-ai-hub-ragaai-catalyst.md) - Python runtime; [kitaru](/tools/zenml-io-kitaru.md) - Python runtime ## Decision facts: RagaAI-Catalyst - **Adopt for:** RagaAI-Catalyst emerges as a specialized Python framework designed for monitoring and evaluating AI agents, with unique features around self-hosted dashboards, advanced analytics, and support for tracing and debugging LL ## Decision facts: kitaru - **Adopt for:** Kitaru focuses on recording, replaying, and enhancing the performance of AI agents in production environments using technology from ZenML. ## Choose when ### Choose RagaAI-Catalyst if… - Tags unique to RagaAI-Catalyst: agentic-ai, agentic-ai-development, agentneo, agents. - When you need comprehensive tools for the observability of complex multi-agentic systems. - More GitHub stars (16k vs 226) - visibility, not fit. ### Choose kitaru if… - Tags unique to kitaru: agent-framework, ai-agents, checkpoints, durable-execution. - - You need to ensure the continuous improvement of AI agents that are already deployed; Kitaru allows you to replay scenarios with different approaches to identify improvements. - More recently updated (last pushed Aug 3, 2026). ## When NOT to use RagaAI-Catalyst - When you prefer a language-agnostic solution or require support outside of the Python ecosystem. - If your primary need is focused solely on basic monitoring without advanced debugging and evaluation features. - For projects that do not utilize multi-agentic systems or do not benefit from timeline and execution graph visualizations. - In scenarios where a fully managed service with no self-hosting requirements is preferred. ## When NOT to use kitaru - - If your project is in the early stages of development without a clear need for replaying historical data or improving upon past behaviors; - - When working outside Python, as Kitaru does not currently offer support for other programming languages. ## Common questions ### What is the difference between RagaAI-Catalyst and kitaru? RagaAI-Catalyst: Python SDK for AI agent observability and evaluation. 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 RagaAI-Catalyst over kitaru? Choose RagaAI-Catalyst over kitaru when Tags unique to RagaAI-Catalyst: agentic-ai, agentic-ai-development, agentneo, agents; When you need comprehensive tools for the observability of complex multi-agentic systems; More GitHub stars (16k vs 226) - visibility, not fit. ### When should I choose kitaru over RagaAI-Catalyst? Choose kitaru over RagaAI-Catalyst when Tags unique to kitaru: agent-framework, ai-agents, checkpoints, durable-execution; - You need to ensure the continuous improvement of AI agents that are already deployed; Kitaru allows you to replay scenarios with different approaches to identify improvements; More recently updated (last pushed Aug 3, 2026). ### When should I avoid RagaAI-Catalyst? When you prefer a language-agnostic solution or require support outside of the Python ecosystem. If your primary need is focused solely on basic monitoring without advanced debugging and evaluation features. For projects that do not utilize multi-agentic systems or do not benefit from timeline and execution graph visualizations. In scenarios where a fully managed service with no self-hosting requirements is preferred. ### When should I avoid kitaru? - If your project is in the early stages of development without a clear need for replaying historical data or improving upon past behaviors; - When working outside Python, as Kitaru does not currently offer support for other programming languages. ### Is RagaAI-Catalyst or kitaru more popular on GitHub? RagaAI-Catalyst has more GitHub stars (16,148 vs 226). Stars measure visibility, not whether either tool fits your constraints. ### Are RagaAI-Catalyst and kitaru open source? Yes - both are open-source projects on GitHub (RagaAI-Catalyst: Apache-2.0, kitaru: Apache-2.0). ### Where can I find alternatives to RagaAI-Catalyst or kitaru? GraphCanon lists graph-backed alternatives at [RagaAI-Catalyst alternatives](/tools/raga-ai-hub-ragaai-catalyst/alternatives) and [kitaru alternatives](/tools/zenml-io-kitaru/alternatives) ([RagaAI-Catalyst markdown twin](/tools/raga-ai-hub-ragaai-catalyst/alternatives.md), [kitaru markdown twin](/tools/zenml-io-kitaru/alternatives.md)), 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](/compare/raga-ai-hub-ragaai-catalyst-vs-zenml-io-kitaru.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, RagaAI-Catalyst or kitaru? RagaAI-Catalyst: Slowing. 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 RagaAI-Catalyst and kitaru? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [RagaAI-Catalyst trust report](/tools/raga-ai-hub-ragaai-catalyst/trust); [kitaru trust report](/tools/zenml-io-kitaru/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=raga-ai-hub-ragaai-catalyst`](/api/graphcanon/graph?tool=raga-ai-hub-ragaai-catalyst) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_