Open, hybrid data store for scaling AI and analytics workloads.
They need to build scalable, governed data pipelines across hybrid cloud environments.
They require a flexible lakehouse architecture that supports multiple analytical engines simultaneously.
They need to consolidate fragmented data stores while maintaining strict security and compliance standards.
The enterprise-grade complexity and cost model are excessive for simple data storage needs.
The absence of a free tier makes it difficult to learn or prototype personal projects.
AI-powered tools that can replace or augment IBM watsonx.data
IBM watsonx.data follows an enterprise-grade consumption-based pricing model, offering high value for large-scale organizations by reducing infrastructure overhead through efficient storage and compute decoupling.
