Comparison
RagaAI-Catalyst vs kitaru
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.
Markdown twin · RagaAI-Catalyst alternatives · kitaru alternatives
GraphCanon updated 2d
vs
Trust & integrity
| Signal | RagaAI-Catalyst | kitaru |
|---|---|---|
| Maintenance | Slowing (189d since push) As of 2d · github_public_v1 | Very active (0d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2d · github_public_v1 | Not a fork · Organization account As of 2w · github_public_v1 |
| OSV dependency advisories | Published findings As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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
- RagaAI-Catalyst
- Python SDK for AI agent observability and evaluation
- kitaru
- Record, replay, and improve AI agents in production, built on ZenML
Stars
- RagaAI-Catalyst
- 16k
- kitaru
- 226
Forks
- RagaAI-Catalyst
- 3.6k
- kitaru
- 15
Open issues
- RagaAI-Catalyst
- 34
- kitaru
- 49
Language
- RagaAI-Catalyst
- Python
- kitaru
- Python
Adopt for
- RagaAI-Catalyst
- 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
- Kitaru focuses on recording, replaying, and enhancing the performance of AI agents in production environments using technology from ZenML.
Persona
- RagaAI-Catalyst
- -
- kitaru
- -
Runtime
- RagaAI-Catalyst
- -
- kitaru
- -
License
- RagaAI-Catalyst
- Apache-2.0
- kitaru
- Apache-2.0
Last pushed
- RagaAI-Catalyst
- Feb 11, 2026
- kitaru
- Aug 3, 2026
Categories
- RagaAI-Catalyst
- AI Agents, Evaluation & Observability
- kitaru
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- RagaAI-Catalyst
- Slowing (36%)
- kitaru
- Very active (96%)
Days since push
- RagaAI-Catalyst
- 189d
- kitaru
- 0d
Open issues (now)
- RagaAI-Catalyst
- 34
- kitaru
- 49
Stars delta
- RagaAI-Catalyst
- +5 (30d)
- kitaru
- Unknown
Open issues delta
- RagaAI-Catalyst
- 0 (30d)
- kitaru
- Unknown
OSV dependency advisories
- RagaAI-Catalyst
- Published findings
- kitaru
- No lockfile (source not queried)
Full report
- RagaAI-Catalyst
- Trust report
- kitaru
- Trust report
Shared compatibility
- Python · RagaAI-Catalyst: Python runtime · kitaru: Python runtime
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.
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.
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 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (raga-ai-hub/RagaAI-Catalyst) · observed Aug 20, 2026
- GitHub forks (raga-ai-hub/RagaAI-Catalyst) · observed Aug 20, 2026
- Last push (raga-ai-hub/RagaAI-Catalyst) · observed Feb 11, 2026
- License file (Apache-2.0) · observed Aug 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (zenml-io/kitaru) · observed Aug 3, 2026
- GitHub forks (zenml-io/kitaru) · observed Aug 3, 2026
- Last push (zenml-io/kitaru) · observed Aug 3, 2026
- License file (Apache-2.0) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: RagaAI-Catalyst 16k · kitaru 226 (synced Aug 20, 2026).
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 and kitaru alternatives (RagaAI-Catalyst 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, 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; kitaru trust report.