openlit vs RagaAI-Catalyst
RagaAI-Catalyst is much bigger: 16.2k stars against 2.7k. Over the days we have tracked them openlit moved +9.2% and RagaAI-Catalyst +0.5%, so openlit is growing faster right now.
openlit leads on context depth. RagaAI-Catalyst does not take any axis by a clear margin.
Stars and commit dates come from our own daily tracking. The six axes are read off each project's documentation by our review pipeline, so they describe what a project says about itself, not what we measured in its code.
Where they stand today
OpenLIT provides an OpenTelemetry-native, open-source AI observability platform combining traces, built-in evaluations, a rule engine, prompt management and guardrails in one stack.
- Stars
- 2.7k
- Tracked growth
- +9.2%
- Maturity
- ●●●●●
- Last commit
- 14m ago
- Language
- TypeScript
- License
- Apache-2.0
- Cost to run
- Self-hosted; you pay for LLM/provider API usage.
Combines agent/LLM tracing, evaluation, guardrails and red‑teaming with a self‑hosted dashboard and execution-timeline analytics for multi-agent debugging.
- Stars
- 16.2k
- Tracked growth
- +0.5%
- Maturity
- ●●●●●
- Last commit
- 208d ago
- Language
- Python
- License
- Apache-2.0
- Cost to run
- Requires RagaAI account; external LLM usage billed to your provider.
Six axes, head to head
Each axis runs 0 to 5. The label under a score is what that project's own docs claim, not a category average.
| Axis | openlit | RagaAI-Catalyst |
|---|---|---|
Context depth How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository. | ●●●●● Full-stack traces | ●●●●● Diff/file only |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● Rule engine filters | ●●●●● Configurable thresholds |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Rules & prompts | ●●●●● Custom rules & prompts |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Self-hostable | ●●●●● Self-hostable |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● Bring-your-key | ●●●●● Bring-your-key |
Setup ease What it takes to get a first useful run out of it. | ●●●●● Docker + config | ●●●●● API key + config |
Which one to pick
Pick openlit if…
Open-source, self-hostable — choose OpenLIT when you need vendor-neutral, full-stack LLM observability plus integrated evaluations, rule-driven guardrails, and prompt/version management.
- Context depth: Full-stack traces (5/5 against 1/5)
Pick RagaAI-Catalyst if…
Comprehensive observability — pick this when you need end-to-end tracing, evaluation and guardrails for agentic systems with an optional self-hosted dashboard and red‑teaming tools.
What people want from each one
openlit/openlit
Hacker News: Show HN: OpenLIT – Open-Source LLM Observability with OpenTelemetry drew 62 points and 22 comments.
raga-ai-hub/RagaAI-Catalyst
Questions people ask
Is openlit better than RagaAI-Catalyst?
openlit leads on context depth. RagaAI-Catalyst does not take any axis by a clear margin. openlit is worth picking when open-source, self-hostable — choose OpenLIT when you need vendor-neutral, full-stack LLM observability plus integrated evaluations, rule-driven guardrails, and prompt/version management.
Which of openlit and RagaAI-Catalyst keeps my code private?
openlit: Self-hostable (4/5). RagaAI-Catalyst: Self-hostable (4/5).
What does each one cost to run?
openlit: Self-hosted; you pay for LLM/provider API usage.. RagaAI-Catalyst: Requires RagaAI account; external LLM usage billed to your provider..
Full profiles: openlit/openlit and raga-ai-hub/RagaAI-Catalyst. Everything else in Observability & tracing.