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Amazon Redshift

Infraestructura de Datos · aws.amazon.com/redshift/

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Resumen

Amazon Redshift is AWS's managed, columnar cloud data warehouse for running large-scale SQL analytics and BI workloads. It separates compute from storage, offers both a serverless mode and provisioned clusters (including newer Graviton-based RA3/RG node types), and integrates natively with the broader AWS data ecosystem including S3, Kinesis, SageMaker, and Bedrock. It reached general availability in February 2013 and remains actively developed with regular AWS feature releases.

El problema que resuelve Amazon Redshift

Analytics teams running large-scale BI and reporting workloads typically outgrow their transactional databases and end up needing separate infrastructure just to store, index, and query billions of rows without slowing down production systems. Amazon Redshift solves this by providing a fully managed, columnar cloud data warehouse that separates compute from storage, scales elastically through Serverless or provisioned clusters, and plugs directly into the rest of the AWS data ecosystem, so analysts can run petabyte-scale SQL analytics without operating their own database servers.

Contexto para decidir

Usa estos puntos para comprobar si el producto encaja con tu operación, no solo con la lista de funciones.

  • Precio de entrada publicado: $0 per RPU-hour (Redshift Serverless base compute rate). Confirma límites de usuarios, uso y funciones por plan.
  • Despliegue: cloud. Comprueba requisitos de seguridad, residencia de datos y acceso para todos los equipos que lo utilizarán.
  • Integraciones verificadas: Amazon S3, Amazon SageMaker, Amazon Bedrock, Amazon Kinesis Data Streams, Amazon MSK, Amazon Aurora. Valida el sentido de sincronización y los límites del plan elegido.
  • La ficha se comprobó por última vez el 31/7/2026; los precios y las funciones pueden cambiar.

Cómo evaluar Amazon Redshift

Una ficha ayuda a crear una lista corta; una prueba con el flujo real del equipo decide si la herramienta encaja. Usa esta lectura junto con los datos estructurados y confirma cualquier cambio con el proveedor.

Encaje de flujo

El registro la considera especialmente adecuada para Organizations already standardized on AWS that want a native, tightly-integrated data warehouse, Enterprises and mid-market companies running large-scale SQL-based BI/reporting workloads, Teams that need to query both data-lake files (S3/Iceberg/Parquet) and warehouse tables from a single SQL engine. Comprueba que ese contexto coincide con el volumen, los roles y los procesos que debe soportar tu equipo.

Preguntas del piloto

  • ¿Puede Amazon Redshift completar el flujo crítico sin trabajo manual fuera de la herramienta?
  • ¿Las conexiones registradas (Amazon S3, Amazon SageMaker, Amazon Bedrock, Amazon Kinesis Data Streams) cubren el sentido de sincronización, los permisos y el volumen que necesitamos?
  • ¿Qué límites de usuarios, uso, almacenamiento, soporte o seguridad aparecen después del precio inicial?

Evidencia y vigencia

Esta ficha se comprobó el 31/7/2026. La fecha indica cuándo se revisó el registro, no una garantía de que el proveedor no haya cambiado sus condiciones después.

Ideal para

  • Organizations already standardized on AWS that want a native, tightly-integrated data warehouse
  • Enterprises and mid-market companies running large-scale SQL-based BI/reporting workloads
  • Teams that need to query both data-lake files (S3/Iceberg/Parquet) and warehouse tables from a single SQL engine

No encaja si

  • Small teams wanting a fully cloud-agnostic warehouse with minimal tuning, since Snowflake/BigQuery are often cited as more portable and lower-maintenance
  • Teams without in-house SQL/DBA expertise, since getting expected performance still requires attention to distribution keys, sort keys, and vacuum/analyze maintenance

Por qué está listada

  • One of the most widely adopted cloud data warehouses, particularly among organizations already standardized on AWS
  • Backs BI/reporting and machine-learning workloads at enterprise scale with deep native integration into the AWS data ecosystem
  • Actively developed AWS service with regular price-performance and architecture updates

Precios

Redshift Serverless

$0 per RPU-hour (billed per-second, 60-second minimum)

Usage-based, auto-scaling compute measured in Redshift Processing Units, with no cluster management required.

  • Automatic scaling of compute capacity
  • Per-second billing
  • No cluster provisioning required
  • Includes Redshift Managed Storage

Provisioned RA3 nodes

$3 per node-hour, e.g. ra3.4xlarge

Current-generation provisioned clusters with managed storage that scales independently of compute.

  • Managed storage billed separately
  • Reserved Instance pricing available
  • Cross-cluster and cross-account data sharing

Provisioned RG (Graviton) nodes

$1 per node-hour, starting price

Newer Graviton-processor-based provisioned instance family, a faster, cheaper successor to RA3.

  • Up to 2.4x the performance of RA3
  • About 30% lower price per vCPU than RA3
  • Managed storage included

Free Trial

Free

Introductory offer for new accounts to evaluate Redshift before paying for compute and storage.

  • $300 credit valid for 90 days for new Serverless users
  • 2-month free trial of a provisioned cluster where Serverless is unavailable

Funciones

AI featuresRedshift ML and Bedrock/Amazon Q integration; AI capability comes via integration with other AWS services
Data governance & lineageRow/column-level security, dynamic data masking, and AWS Lake Formation integration
Data pipelines / ETLNot a dedicated pipeline/orchestration tool, but supports zero-ETL integrations and native streaming ingestion
Pre-built connectorsJDBC/ODBC drivers, Data API, federated query, and native connectors for major BI tools
Public APIRedshift Data API allows running SQL over HTTPS, alongside standard AWS SDK/CLI access
Role-based access controlIAM-based access control plus native database users/roles/groups and fine-grained permissions
Scheduling & triggersBuilt-in query scheduling, materialized view auto-refresh, and EventBridge integration
Self-hosting / on-premFully managed AWS cloud service; no general self-hosted or on-prem deployment option
Workflow automationNo native workflow-builder, but integrates with AWS Step Functions, EventBridge, and Glue

Integraciones

Amazon S3Amazon SageMakerAmazon BedrockAmazon Kinesis Data StreamsAmazon MSKAmazon AuroraAmazon RDSAmazon DynamoDBAWS Data ExchangeAWS GlueAmazon QuickSightTableauMicrosoft Power BILookerdbtFivetran

Seguridad y cumplimiento

SOC 1SOC 2PCI DSSISO 27001ISO 27017ISO 27018ISO 9001HIPAA (eligible service)FedRAMP

Pros y contras

Pros

  • Deep, native integration with the AWS ecosystem (S3, Kinesis, SageMaker, QuickSight, Bedrock)
  • Strong price-performance, especially with newer RA3/RG (Graviton) node types and the Serverless option
  • Scales to petabyte-size datasets while remaining standard SQL/JDBC/ODBC compatible
  • Mature, extensively documented security/compliance footprint (SOC 1/2, PCI DSS, ISO 27001, HIPAA-eligible)

Contras

  • Reviewers note a real learning curve around performance tuning (distribution keys, sort keys, vacuum/analyze)
  • Node-based provisioned pricing and concurrency limits can get expensive at scale compared to some competitors
  • Some SQL syntax and behavior differences from standard PostgreSQL trip up newcomers
  • Less cloud-agnostic than Snowflake or BigQuery — tightly coupled to the broader AWS ecosystem

Qué muestra el registro

4.3/5
402 reviews agregadasÚltima comprobación 2026-07-31
G2 ↗Capterra ↗TrustRadius ↗

Rated 4.3/5 on G2 (402 reviews) and 4.4/5 on Capterra (14 reviews); reviewers consistently cite strong scalability and AWS-ecosystem integration, with support quality and data-security sub-scores of 8.5 and 9.7 on G2 respectively.

Resumen y puntuación agregados de plataformas públicas de reseñas. Enlazamos a las reseñas originales en lugar de reproducirlas — lee la fuente antes de decidir.

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