CData Virtuality vs. Denodo

Industry experts and data enthusiasts agree: There's simply no comparison to CData Virtuality.

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Crédit Agricole
B/S/H
PGGM
Cyberport
Iris
Unanet
Crédit Agricole
B/S/H
PGGM
Cyberport
Iris
Unanet

4 reasons CData Virtuality delivers better price-performance


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Maximize value, minimize cost!

CData Virtuality's entry-level plans are 40% more affordable and include features like version control, ETL/ELT, data catalog, and connections to up to 20 data sources (compared to 5 in Denodo's plan). The Enterprise plan delivers even greater value, costing up to 55% less than Denodo's.

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2-in-1 logical & physical data integration

CData Virtuality connects to 300+ data sources and seamlessly integrates data virtualization, ETL/ELT, and streaming, providing maximum flexibility in data management with a single tool.

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Cut costs & scale with hybrid & multi-cloud flexibility

Achieve cost efficiency with hybrid and multi-cloud architecture, enabling flexible workload distribution and smarter budget management. Seamless integration of diverse cloud environments reduces single-provider dependency and supports cost-effective scalability.

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Quickest time-to-value & low administration due to SaaS

CData Virtuality ensures accessibility and ease of use with a fully managed SaaS solution that accelerates time-to-market and minimizes maintenance and administration efforts. On-premises and VPC deployments are still available.

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CData Virtuality powers data management initiatives for enterprises worldwide


Crédit Agricole Cuts Costs by 80% and Speeds Time-to-Market

“Now that the developers as well as business analysts can use the solution, we are not only more efficient, but also cut costs by 80%.”

— Fred Dunant
Manager, Data Management Office, Crédit Agricole


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Crédit Agricole logo

PGGM Streamlines Data Delivery Processes

“We significantly reduced time-to-market from weeks or months to several hours or even minutes while ensuring data governance — who has access to what, why do they have access, and is the data used securely.”

— Marco van der Winden
Manager, Corporate Data Management, PGGM


Read case study
PGGM logo

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Dive deeper into 40+ insightful comparisons between CData Virtuality and Denodo across features, prices and use cases

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Denodo Platform
Deployment Options
On-premise
Virtual private cloud (VPC)

(available on AWS and Azure Marketplace)
Fully-managed (SaaS)
Data Connectivity
Source connectors (to APIs, databases and files)
20 connections
(choose from 300+ connectors)
Max 5 sources
(choose from 150+ connectors)
Data consumer interfaces
ODBC, JDBC, Odata, and REST-API support
ODBC, JDBC, Odata, GraphQL, SOAP, OpenAPI and REST-API
Data Integration Functionality
Data virtualitzation
Data replication (ETL / ELT) supporting Slowly Changing Dimension Type 2, CopyOver, Incremental, Upsert, and Batch
Streaming Data Integration (e.g., Kafka)
Use Massively Parallel Processing (MPP) engines for query acceleration
View all features

Competitive data on this page was collected as of October 23, 2024, and is subject to change or update. CData does not make any representations as to the completeness or accuracy of the information on this page. If you spot any inaccuracies or need clarifications, please feel free to reach out to us at info@cdata.com

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Denodo Platform
Starting price (per year)
$29,990 USD
(10 Concurrent Queries / 2 CPU-Cores)
$50,000 USD
(4 Core-CPU)
Main pricing metric
Concurrent Queries or CPU-Cores
CPU-Cores
Key limitations
  • 20 Connections / no premium connectors
  • No version control
  • No MPP support
  • No clustering
  • Max 5 different sources
  • Limited connectivity (only 150 connectors)
  • No ETL/ELT
  • No version control
  • No SaaS
  • No MPP support
  • No query acceleration
  • No stored procedures
  • No data catalog
  • No global security policies
Minimum contract length
Annually
Hourly through AWS/Azure Marketplace
Pay-as-you-go (Agora)
Free trial
30 days
30 days free license, but compute/storage cost applies

Sources: CData Virtuality pricing page and AWS Marketplace for Denodo

In summary, both CData Virtuality and Denodo have distinct pricing and features to consider.

Entry level plans:

CData Virtuality's Standard Plan: Priced at $29,990 USD per year. It includes essential features such as support for more than 5 sources, version control, and support for stored procedures.

Denodo's Professional Plan: Priced at $50,000 USD per year.

Enterprise plans:

CData Virtuality: Starts at $99,990 USD and offers features like ETL/ELT.

Denodo's Enterprise Plus Plan: Starts at $225,750 USD. While it does not have ETL/ELT, it does offer a comprehensive Data Catalog. CData Virtuality has basic Data Catalog functionality and can natively integrate with specialized catalog vendors like Dataspot.

Pricing structure:

CData Virtuality: Bases its pricing on "Concurrent Queries" for the cloud hosted version (SaaS) and CPU-cores for on-premise environments, allowing users to scale based on their needs.

Denodo: Uses a tiered CPU pricing model. The entry tier comes with 4 CPU-cores. Subsequent tiers, like the one with 8 CPU-cores, offer increased performance.

Trials and free versions:

Both platforms extend trial versions for users. Additionally, Denodo provides "Denodo Express" as a free version for single users. This version supports up to 3 concurrent queries with a cap of 10,000 results per query. Additional compute/storage costs are associated with this version.

Compare use cases

Denodo Platform
Data Fabric
The Data Fabric is a design concept that harmonizes disparate data sources across hybrid and multi-cloud environments, using metadata, analytics, and machine learning to enable seamless data access, discovery, and actionable insights for improved decision-making.
Data Mesh
Data Mesh is a socio-technical data management paradigm that decentralizes data ownership and treats data as a product, focusing on domain-specific ownership, self-serve data infrastructure platforms, and federated computational governance to enable scalable, sustainable, and business-centric data architecture, challenging traditional monolithic and technology-focused approaches.
Self-Service Semantic Layer
Provide a central data access layer to cleanse, enrich, and govern data for all data consumers.
Hybrid- and Multi-Cloud integration
Seamlessly integrate and manage data across diverse cloud environments, reducing single-provider dependency while ensuring data quality, governance, and cost-effective scalability.
Partially — "lift and shift" migration of data to the cloud is not possible.
Customer Data Integration
Centralize customer data from databases and APIs to gain a 360 degree customer view.
Partially — Denodo cannot replicate data from APIs to ensure historical analysis and minimizing direct API calls.
Data Governance
A robust data governance framework promotes data democratization and accessibility across an organization by systematically coordinating data access, security controls, and ownership through designated data stewards and owners. Data virtualization acts as a layer of abstraction, allowing organizations to implement and enforce data security and compliance policies consistently across multiple data sources and platforms.
Data Services
Provide developers with central data access via API across disparate sources.

Frequently asked questions

We implement SSL/TLS, SSH Tunnels, SSO, LDAP, Active Directory, OAuth, SAML, OpenID Connect, and Kerberos for robust data security and comply with industry standards such as ISO 27001 and SOC2 (see Trust Center).

CData Virtuality scales to meet growing data demands through a multi-layered approach:

  1. Concurrent Queries: Initially, scalability is achieved by increasing the number of concurrent queries on a single instance.
  2. Clustering and Kubernetes/Container-Based Setups:
    • Clustering: As demand grows, additional instances can be clustered to distribute the workload, ensuring high availability and fault tolerance. This is ideal for environments requiring robust failover and load balancing.
    • Kubernetes/Container-Based Setups: Utilizes Kubernetes and containerization for managing and scaling deployments efficiently. This approach offers advanced orchestration, automation, and dynamic scaling capabilities, making it suitable for environments with fluctuating workloads and greater flexibility. Kubernetes can manage clustered environments to provide even greater resilience and scalability.
  3. Massively Parallel Processing (MPP): For large-scale data operations, MPP allows for offloading processing tasks to multiple processors, enhancing performance and throughput.

We provide 18/5 support for all plans, with enterprise customers having access to advanced support and a dedicated solution engineer for the first 90 days. Extended Premium Support plans are available on request.

Setting up and integrating CData Virtuality is straightforward and efficient. Most data sources can be connected in minutes if credentials are available. For the first 90 days, a dedicated solution engineer will support you to ensure a smooth onboarding process. The overall setup timeline varies from a few days to a few months, depending on project complexity, infrastructure readiness, and security requirements. With a well-prepared project, initial results can often be achieved in just a few days.

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