CData Virtuality 製品価格

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 high 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.

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.