Denodo for AWS (Consumption Based Pricing)

Denodo for AWS leads with agentic AI to accelerate data access and cloud adoption for all, powered by data virtualization, integrates and delivers data from AWS, SaaS and other data sources.

It creates a centralized logical data access and management layer that decouples data access from the complexity of the underlying data sources, regardless of where the data resides, to create business-friendly views of all enterprise data.

It powers data integration with AI/ML driven automatic recommendation of datasets, infrastructure management and smart query optimization.

Take advantage of the consumption based pricing based on volume of data retrieved from the data sources and the number of data products published as business views via the Denodo Data Marketplace.

Customers now have the ability to choose from three different tiers. All paid tiers add advanced performance and acceleration, including the Data Lakehouse Acceleration Engine:

• Team Tier: empower small teams to deliver focused data projects with fast time-to-value. It comes with single server support up to 8 cores and with 100 data products and 7.5TB/year.
• High Availability Tier: support growing workloads with reliable performance across multiple projects and teams. It includes clustering capabilities and comes with 225 data products and 25 TB/year.
• Business Critical Tier: unify data at full enterprise scale with resilient mission-critical operations It includes clustering capabilities and comes with 750 data products and 75 TB/year.

Key Features:

Unified data access across hybrid and multicloud environments

• Get live, zero-copy access to operational and analytical data across your entire data estate.
• Gain a single, trusted view of data across on-premises, multi-cloud, and sovereign environments (200+ systems).

Universal semantic layer and trusted business context

• Establish a consistent, shared semantic layer across Amazon SageMaker Lakehouse, AWS data services, on-premises systems, and multi-cloud environments.
• Deliver a unified business view with common definitions, metrics, and relationships, ensuring AI and analytics operate on trusted meaning and context.

Strong governance and security

• Enforce consistent security and governance across all data, with Denodo governing non-AWS sources alongside Amazon SageMaker's native controls for AWS data.
• Protect sensitive data and reduce risk using fine-grained access controls, dynamic masking, and end-to-end data lineage across hybrid and multi-cloud environments.

AI-ready data foundation

• Build and run AI agents on Amazon SageMaker and Amazon Bedrock, with Denodo delivering governed, real-time data access with embedded context, lineage, and policy controls.
• Ensure AI models and agents access trusted, compliant, and relevant data for reliable decision-making and autonomous actions at scale.
• Turn business context into live, zero-copy, policy-controlled data access using MCP, text-to-SQL, and metadata embeddings instead of bulk data movement.

Key Use Cases for Denodo on AWS:

• AI-ready data for intelligent AI agents: A universal semantic layer unifies all enterprise data in real time, providing context-rich, trusted information that enables AI agents to deliver accurate insights and take autonomous actions, accelerating decisions and driving measurable business impact.
• Unified analytics for hybrid and multicloud: Users can query distributed data sources in real-time as if they were part of one unified logical data layer without copying data or building complex ETL (extract, transform, load) pipelines. Teams can use consistent, trustworthy datasets for analytics with significantly less effort.
• Self-service access to enterprise data (e.g., SAP, Oracle): Business users and analysts can get live, self-service access to data in enterprise applications such as SAP and Oracle without relying on IT. Users can easily explore application data and selectively retrieve datasets for analysis in their preferred AWS services or tools.
• Workload migration and cloud modernization: With a logical data abstraction layer, your organization can migrate to AWS services and modernize architecture seamlessly, isolating reports and applications from backend changes to avoid operational disruptions and accelerate cloud adoption.