--- title: "openlit vs whylogs" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/openlit-openlit-vs-whylabs-whylogs" tools: ["openlit-openlit", "whylabs-whylogs"] --- # openlit vs whylogs *GraphCanon updated Aug 2, 2026* ## Verdict Pick openlit if decision-critical facts for OpenLIT are centered around its unique features in LLM observability, GPU monitoring, and extensive integration capabilities; pick whylogs if whylogs is an open-source data logging library that provides detailed data quality monitoring and model performance tracking over time. It supports privacy-preserving data collection to ensure robust and safe operations. [openlit](https://docs.openlit.io) reports 2.7k GitHub stars, 342 forks, and 48 open issues, last pushed Jul 31, 2026. [whylogs](https://whylogs.readthedocs.io/) has 2.8k stars, 143 forks, and 4 open issues, last pushed Jan 10, 2025. Figures are from public GitHub metadata via [openlit's repository](https://github.com/openlit/openlit) and [whylogs's repository](https://github.com/whylabs/whylogs). | | [openlit](/tools/openlit-openlit.md) | [whylogs](/tools/whylabs-whylogs.md) | | --- | --- | --- | | Tagline | A comprehensive open-source platform for AI Engineering with LLM Observability, Monitoring, and Management | An open-source data logging library for ML models and data pipelines. | | Stars | 2,664 | 2,830 | | Forks | 342 | 143 | | Open issues | 48 | 4 | | Language | TypeScript | Jupyter Notebook | | Adopt for | Decision-critical facts for OpenLIT are centered around its unique features in LLM observability, GPU monitoring, and extensive integration capabilities. | whylogs is an open-source data logging library that provides detailed data quality monitoring and model performance tracking over time. It supports privacy-preserving data collection to ensure robust and safe operations. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Evaluation & Observability, Inference & Serving | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [openlit](/tools/openlit-openlit.md) | [whylogs](/tools/whylabs-whylogs.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 568d | | Open issues (now) | 48 | 4 | | Full report | [trust report](/tools/openlit-openlit/trust.md) | [trust report](/tools/whylabs-whylogs/trust.md) | ## Shared compatibility - **Python**: [openlit](/tools/openlit-openlit.md) - Python runtime; [whylogs](/tools/whylabs-whylogs.md) - Python runtime ## Decision facts: openlit - **Pricing:** freemium - **Adopt for:** Decision-critical facts for OpenLIT are centered around its unique features in LLM observability, GPU monitoring, and extensive integration capabilities. - **License detail:** Apache-2.0 ## Decision facts: whylogs - **Adopt for:** whylogs is an open-source data logging library that provides detailed data quality monitoring and model performance tracking over time. It supports privacy-preserving data collection to ensure robust and safe operations. ## Choose when ### Choose openlit if… - openlit is primarily TypeScript; whylogs is Jupyter Notebook. - Tags unique to openlit: ai-observability, gpu-monitoring, langchain, llmops. - Also covers Inference & Serving. - When you need comprehensive observability features native to OpenTelemetry, allowing seamless trace and metric management with an out-of-the-box solution. ### Choose whylogs if… - whylogs is primarily Jupyter Notebook; openlit is TypeScript. - Tags unique to whylogs: ai-pipelines, analytics, approximate-statistics, calculate-statistics. - When you need comprehensive data visibility to track changes in datasets and model input features for ML systems ## When NOT to use openlit - If your project strictly requires a proprietary tool or if you have specific requirements that are not covered by OpenLIT's integrations, such as unique vector databases not yet supported. - When the team lacks the expertise in TypeScript or Python SDK to efficiently manage and implement observability into their current workflows with OpenLIT. ## When NOT to use whylogs - When limited to using closed-source tools as whylogs is open source under the Apache-2.0 license - In environments where privacy-preserving features are not required or can be handled through other means ## Common questions ### What is the difference between openlit and whylogs? openlit: A comprehensive open-source platform for AI Engineering with LLM Observability, Monitoring, and Management. whylogs: An open-source data logging library for ML models and data pipelines.. See the comparison table for live GitHub stats and shared categories. ### When should I choose openlit over whylogs? Choose openlit over whylogs when openlit is primarily TypeScript; whylogs is Jupyter Notebook; Tags unique to openlit: ai-observability, gpu-monitoring, langchain, llmops; Also covers Inference & Serving; When you need comprehensive observability features native to OpenTelemetry, allowing seamless trace and metric management with an out-of-the-box solution. ### When should I choose whylogs over openlit? Choose whylogs over openlit when whylogs is primarily Jupyter Notebook; openlit is TypeScript; Tags unique to whylogs: ai-pipelines, analytics, approximate-statistics, calculate-statistics; When you need comprehensive data visibility to track changes in datasets and model input features for ML systems. ### When should I avoid openlit? If your project strictly requires a proprietary tool or if you have specific requirements that are not covered by OpenLIT's integrations, such as unique vector databases not yet supported. When the team lacks the expertise in TypeScript or Python SDK to efficiently manage and implement observability into their current workflows with OpenLIT. ### When should I avoid whylogs? When limited to using closed-source tools as whylogs is open source under the Apache-2.0 license In environments where privacy-preserving features are not required or can be handled through other means ### Is openlit or whylogs more popular on GitHub? whylogs has more GitHub stars (2,830 vs 2,664). Stars measure visibility, not whether either tool fits your constraints. ### Are openlit and whylogs open source? Yes - both are open-source projects on GitHub (openlit: Apache-2.0, whylogs: Apache-2.0). ### Where can I find alternatives to openlit or whylogs? GraphCanon lists graph-backed alternatives at [openlit alternatives](/tools/openlit-openlit/alternatives) and [whylogs alternatives](/tools/whylabs-whylogs/alternatives) ([openlit markdown twin](/tools/openlit-openlit/alternatives.md), [whylogs markdown twin](/tools/whylabs-whylogs/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/openlit-openlit-vs-whylabs-whylogs.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, openlit or whylogs? openlit: Very active. whylogs: Dormant. 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 openlit and whylogs? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [openlit trust report](/tools/openlit-openlit/trust); [whylogs trust report](/tools/whylabs-whylogs/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=openlit-openlit`](/api/graphcanon/graph?tool=openlit-openlit) - 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/_