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SPECIFICTION
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MLRun vs Outerbounds

MLRun

mlrun.org

Outerbounds

outerbounds.com

Side by side

FigureMLRunOuterbounds
Price fromFree$2,499/mo
Free planYesYes
Free trialYesYes
Open source——
WebYesYes
WindowsYes—
macOSYes—
LinuxYes—
APIYesYes
Self-hostedYes—
Plans published23
Spec score · MLOps Platforms7.7 (#9)7.7 (#10)
IntegrationsThe ecosystem lists GitHub Actions, GitLab CI/CD, Jenkins and Kubeflow Pipelines for CI/CD integration.Outerbounds documents Snowflake access and examples for AWS Athena, Amazon SageMaker, and Amazon Bedrock.
PurposeMLRun is an open-source AI orchestration framework for managing machine-learning and generative-AI applications across their lifecycles.Outerbounds provides a managed platform for building and deploying production AI and ML systems in a customer’s cloud.
SecurityManaged MLRun provides LDAP integration, user and group management, service authentication and authorization, and secured API-gateway authentication.The pricing page lists SOC 2 compliance for Starter and Enterprise, and HIPAA support is stated on the product homepage.
SupportThe open-source offering includes community support, while managed MLRun includes 24/7 enterprise support, service monitoring and log management.Starter and Enterprise include dedicated support, while the Community plan lists community support.

Plans

MLRun

  • Open Source MLRunFree
  • Managed MLRun on IguazioPriced on request

MLRun pricing →

Outerbounds

  • CommunityFree
  • Starter$2,499 a month
  • EnterprisePriced on request

Outerbounds pricing →

In their own words

MLRun

MLRun is an open-source framework for orchestrating machine-learning and generative-AI applications across their lifecycles. It automates data preparation, model tuning, customization, validation, and optimization for ML models and large language models over elastic resources. Its feature store can collect, transform, store, catalog, serve, and monitor data features. MLRun supports multi-cloud, hybrid, and on-premises deployments with built-in observability; documented options include Kubernetes, AWS, Azure AKS, and Iguazio’s managed service. The ecosystem includes storage and data systems such as S3, Google Cloud Storage, BigQuery, Snowflake, Kafka, Spark, and Dask, alongside PyTorch, TensorFlow, XGBoost, and ONNX. CI/CD integrations include GitHub Actions, GitLab CI/CD, Jenkins, and Kubeflow Pipelines. MLRun also lists model registry, experiment tracking, pipeline orchestration, model serving, data versioning, and managed compute. The open-source plan costs nothing and includes community support. Managed MLRun includes LDAP integration, user and group management, service authentication and authorization, secured API-gateway authentication, service monitoring, log management, and 24/7 enterprise support.

Visit mlrun.org

Outerbounds

Outerbounds is a managed platform for building and deploying production AI and machine-learning systems in a customer's cloud. It supports data processing, machine learning, AI applications, and agentic workflows, with orchestration, metadata tracking, monitoring, and production deployment tools. Developers can test code locally before deployment; Starter includes up to three cloud workstations. The platform documents Snowflake access and examples for AWS Athena, Amazon SageMaker, and Amazon Bedrock. Outerbounds says it can deploy in any cloud region in less than 15 minutes. Its free Community plan is built around open-source Metaflow, with infrastructure and security managed by the customer. Starter costs $2,499 a month, billed annually, and includes a 30-day trial. Starter is limited to three compute nodes and three workstations. Enterprise lists unlimited compute and workstations, multi-region deployment, and advanced RBAC, with price available by contacting the provider. Starter and Enterprise list SOC 2 compliance and dedicated support; HIPAA support is stated on the product homepage.

Visit outerbounds.com