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Dataiku vs. Explo

Elaborado a partir del registro investigado y revisado de cada herramienta. Las cifras se contrastan con las páginas públicas de precios en el momento de la investigación — confirma siempre el precio actual con el proveedor antes de comprar.

La versión corta

Dataiku parte de Custom pricing por usuario, frente a Explo con Custom pricing.

Comparación completa

Dataikudesde Custom pricing
Explodesde Custom pricing
Audyense Score22AS*Bajo57AS*Aceptable
PosicionamientoCollaborative data science, analytics, and AI platformCustomer-facing analytics for any platform
Plan gratuitoNoNo
ImplementaciónNube / SaaS, Híbrido, Instalación localNube / SaaS
Mejor encajeMediana empresa, EmpresaPYME, Mediana empresa
Planes de precio
  • TeamCustom pricing
  • EnterpriseCustom pricing
Visual data preparationPrepares data through visual workflows.
Code notebooksSupports Python, R, and advanced analysis.
Machine learningBuilds and evaluates models in shared projects.
Model deploymentSupports production endpoints and operational workflows.
AI governanceAdds control and traceability to AI projects.
CollaborationBrings technical and business users into common projects.
Cloud integrationsConnects with major clouds and data platforms.
Hybrid deploymentSupports cloud, on-premise, and controlled environments.
Embedded dashboards
White-label styling
AI report builder
Direct database/warehouse connections
Dedicated/region-specific hosting
Integraciones verificadas
Valoración agregada · No reviews yet4.9 · 138 reviews
Integraciones
SnowflakeDatabricksAWSGoogle CloudMicrosoft AzureGit+9 más
Seguridad y cumplimiento
SOC 2ISO 27001GDPR
SOC 2 Type IIHIPAA
Pros
  • Visual and code-based workflows
  • Strong governance and collaboration
  • Broad cloud and model ecosystem
  • Production-oriented platform
  • Makes analytics simple, customizable, and scalable without slowing down dev teams
  • Fast deployment for embedding dashboards
  • Flexible feature set for securely sharing data with customers
Contras
  • Enterprise pricing and implementation
  • Large feature surface
  • Requires operating-model alignment
  • May exceed the needs of a small data team
Visitar Dataiku ↗Visitar Explo ↗