Registro lado a lado

Databricks vs. Rivery

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

Databricks parte de Free por usuario, frente a Rivery con $1. Rivery tiene la valoración agregada más alta (4.7/5 frente a 4.6/5).

Comparación completa

	Databricksdesde Free	Riverydesde $1 per BDU credit
Audyense Score	81ASSólido	61AS*Aceptable
Posicionamiento	Unified data, analytics, and AI platform built on the lakehouse	Usage-based ETL, ELT, orchestration, and reverse ETL for modern data teams.
Plan gratuito	Sí	No
Implementación	Nube / SaaS	Nube / SaaS
Mejor encaje	Mediana empresa, Empresa	PYME, Mediana empresa, Empresa
Planes de precio	Free EditionFree Standard compute (Jobs)$0 SQL Serverless$1 Enterprise$0	Base$1 ProfessionalCustom pricing Pro PlusCustom pricing EnterpriseCustom pricing
Workflow automation	SíDatabricks Workflows/Lakeflow Jobs natively orchestrate notebooks, pipelines, and ML tasks with dependencies and retries.	—
AI features	SíMosaic AI, Databricks Assistant, AI/BI Genie, and Model Serving provide built-in generative AI and ML tooling.	—
Public API	SíExtensive REST APIs are documented for workspaces, jobs, clusters, and Unity Catalog objects.	—
Self-hosting / on-prem	NoSaaS-only; compute runs inside the customer's cloud account, but there is no on-premises or self-hosted deployment option.	—
Pre-built connectors	ParcialNative ingestion via Auto Loader plus Partner Connect integrations, but not as broad a native connector catalog as dedicated iPaaS/ELT tools.	—
Data pipelines / ETL	SíDelta Live Tables / Lakeflow Declarative Pipelines is a core product for building and managing ETL pipelines.	—
Scheduling & triggers	SíWorkflows support cron scheduling, file-arrival triggers, and event-based triggers.	—
Data governance & lineage	SíUnity Catalog provides centralized governance, lineage, and cataloging across all workspaces.	—
Role-based access control	SíUnity Catalog supports role-based, row/column-level, and attribute-based (ABAC) access control.	—
API and CLI	—	SíAvailable on Professional and above.
ETL and ELT	—	Sí
SSO and SCIM	—	SíAvailable on Pro Plus and above.
Reverse ETL	—	Sí
Private networking	—	SíPrivateLink, VPN, and reverse SSH vary by plan.
Workflow orchestration	—	Sí
Python transformations	—	Sí
Custom data sources	—	Sí
Integraciones verificadas	15+	—
Valoración agregada	4.6 · 658 reviews	4.7 · 120 reviews
Integraciones	FivetrandbtAlationMicrosoft Power BITableauRivery+9 más	SnowflakeAmazon RedshiftGoogle BigQueryDatabricksSalesforceHubSpot+9 más
Seguridad y cumplimiento	SOC 2 Type IIISO 27001HIPAAPCI DSS+1 más	SOC 2 Type IIHIPAA
Pros	Strong at unifying data engineering, data science, and BI/analytics under one governed platform Delta Lake and Unity Catalog provide robust data reliability, lineage, and access control Scales well for very large datasets and complex ML/AI workloads Native integrations across major BI tools (Tableau, Power BI, Looker) and ingestion tools (Fivetran, dbt)	One product covers extraction, transformation, orchestration, and reverse ETL. No per-connector or per-user charge on most plans. Python, custom sources, API/CLI, branching, dependencies, and built-in versioning support engineering workflows. PrivateLink, VPN, SSO, SCIM, audit logs, and custom file zones cover serious governance needs.
Contras	Steep learning curve, especially for teams new to Spark or lakehouse concepts Usage-based DBU pricing is complex and can scale unpredictably Non-technical users find the interface and setup less approachable than simpler BI tools Managing and forecasting compute cost requires ongoing FinOps discipline	BDU/RPU pricing requires workload measurement rather than simple seat budgeting. Base is limited to two users and one environment; larger teams need higher tiers. Enterprise security and connectivity features are not available at the entry level. Less ecosystem maturity and review volume than the largest data-integration incumbents.
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