VMware Tanzu Data Solutions and Actian Ingres are competing products in the data management category. VMware Tanzu Data Solutions seems to hold the upper hand due to its strong pricing and support, while Actian Ingres is noted for its advanced features.
Features: VMware Tanzu Data Solutions offers comprehensive integration with cloud environments, along with modern data service capabilities and efficient resource management. Actian Ingres is known for its robust scalability, performance optimization, and efficient handling of data-intensive applications.
Ease of Deployment and Customer Service: VMware Tanzu Data Solutions provides flexible deployment options and strong customer support, making implementation seamless. Actian Ingres features a straightforward deployment model but faces initial support challenges, indicating potential areas for improvement in customer service.
Pricing and ROI: VMware Tanzu Data Solutions involves a higher initial setup cost but promises long-term ROI due to its cloud efficiencies. Actian Ingres offers more cost-effective initial pricing, appealing to budget-conscious buyers, though it may require additional investment for performance tuning to achieve maximum ROI.
| Product | Market Share (%) |
|---|---|
| VMware Tanzu Data Solutions | 3.6% |
| Actian Ingres | 1.4% |
| Other | 95.0% |
| Company Size | Count |
|---|---|
| Small Business | 30 |
| Midsize Enterprise | 10 |
| Large Enterprise | 48 |
Actian’s Ingres is a leading, enterprise-grade database management system designed to reduce IT costs and time-to-value, while delivering the strength and features expected from an enterprise-class database. Ingres 10.2 is the latest version of the database, containing enhancements that will make it easier to internationalize customer applications. Along with improved performance and reduced configuration overhead, users can take their first steps into big data analytics with the new Window functions.
VMware Tanzu is a robust platform tailored for data warehousing, complex analytics, BI applications, and predictive analytics. It excels in scalability, performance, and parallel processing, enhancing data handling efficiency. Users report significant productivity improvements and streamlined operations, making it ideal for comprehensive data solutions.
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