Arize Phoenix
6.3#10 in machine learning model monitoring softwareFree planFree planWebAPISelf-hosted
VisitArize Phoenix vs Deepchecks
Deepchecks
8.1#3 in machine learning model monitoring softwareFree planFree planWebAPILinuxmacOS
VisitWhat both publish
| Fact | Arize Phoenix | Deepchecks |
|---|---|---|
| Deployment | Phoenix can run locally or be self-hosted using Docker, Kubernetes, or a cloud environment. | Deployment options listed include multi-tenant SaaS, virtual private cloud on GCP or Azure, bare metal, and AWS-managed deployment. |
| Integrations | Documented integrations include frameworks and providers such as LlamaIndex, LangChain, DSPy, OpenAI, Bedrock, and Anthropic. | The integrations page describes Deepchecks integrations with pytest, Apache Airflow, ZenML, and CML. |
| License | The Phoenix page describes the project as ELv2 licensed. | The deepchecks and monitoring projects are AGPL 3.0, while monitoring enterprise components under the ee directory use a commercial license. |
Arize Phoenix plans
- PhoenixFree
Deepchecks plans
- Open-Source MonitoringFree
- Startup MonitoringPriced on request
- Dedicated MonitoringPriced on request
- EnterprisePriced on request
- BasicPriced on request
- Partnership MonitoringPriced on request
Pick Arize Phoenix if…
Phoenix suits teams building AI applications who need to inspect traces, evaluate outputs, and compare application versions. It offers local and self-hosted deployment for teams managing their own trace data.
Pick Deepchecks if…
Deepchecks suits teams that need to evaluate and monitor AI systems in production, compare versions, and investigate application behavior. Its deployment options and listed security provisions may also suit organizations with specific infrastructure or compliance needs.