CData Virtuality vs. Denodo

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

See why data teams prefer CData Virtuality over Denodo

Time-to-value & deployment flexibility

Unlike Denodo, CData Virtuality allows you to choose a deployment method that works best for your operational requirements. Options include fully-managed SaaS, self-hosted cloud, or on-premises. This ensures a shorter time-to-market, low maintenance, and the flexibility to grow and adapt your data virtualization solution as needed.

Maximize value, minimize cost

Decentralize data ownership for a scalable, domain-centric, business-focused architecture.

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Support for a multitude of data management use cases

Create a unified data model, enabling standardized enterprise-wide analytics.

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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 cost by 80%.”

— Fred Dunant
Manager, Data Management Office, Crédit Agricole

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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

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Frequently asked questions

What security measures are in place to protect our data?

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).

What are the scalability options for growing data needs?

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

Concurrent Queries: Initially, scalability is achieved by increasing the number of concurrent queries on a single instance.
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 high flexibility. Kubernetes can manage clustered environments to provide even greater resilience and scalability.
Massively Parallel Processing (MPP): For large-scale data operations, MPP allows for offloading processing tasks to multiple processors, enhancing performance and throughput.

What support options are available, and how quickly can we get help?

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.

How easy is it to set up and integrate the data virtualization platform?

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.

What kind of training do I need to productively work with CData Virtuality?

To productively work with Data Virtuality's solutions, having some foundational knowledge is beneficial. The platform is designed for sophisticated data management use cases but is accessible to both technical and non-technical users.

Recommended Knowledge:

SQL: Basic to intermediate understanding of SQL is highly recommended
Data Virtualization Concepts: Familiarity with data virtualization principles will help you leverage the platform effectively.
Relational Databases: Experience working with relational databases is beneficial.

Training and Support:

During onboarding, you can schedule training sessions with our Solution Engineer to get up to speed.
These sessions are designed to provide hands-on experience and address any specific queries you may have.

With the recommended knowledge and the available training sessions, non-technical users can quickly acquire the skills needed to operate Data Virtuality's solutions efficiently.