IBM watsonx.data
από IBM Software
IBM® watsonx.data™ data enables you to scale analytics and AI with all your data, wherever it reside
IBM watsonx.data is an open, hybrid, and governed data store built on an open data lakehouse architecture. The data lakehouse is an emerging architecture that offers the flexibility of a data lake with the performance and structure of a data warehouse. Watsonx.data is an enterprise-ready data store that enables hybrid cloud analytics workloads such as data engineering, data science and business intelligence, through open-source components with integrated IBM innovation.
Watsonx.data will allow users to access their data through a single point of entry and run multiple fit-for-purpose query engines such as Presto and Spark across IT environments. Through workload optimization an organization can reduce data warehouse costs by up to 50 percent by augmenting with this solution. It also offers built-in governance, automation and integrations with an organization's existing databases and tools to simplify setup and user experience.
Db2 Warehouse and Netezza on Azure natively integrate with watsonx.data with shared metadata and support for open formats such as Parquet and Iceberg to share and combine data for new insights without ETL. Watsonx.data allows customers to augment data warehouses such as Db2 Warehouse and Netezza and optimize workloads for performance and cost.
For trials and customized IBM watsonx.data pricing contact your IBM Sales Representative or email us.
Visit https://www.ibm.com/products/watsonx-data to learn more about our consumption model and product editions.
For more information on IBM watsonx.data visit https://www.ibm.com/products/watsonx-data.
Access all your data across hybrid-cloud: Access all data through a single point of entry with a shared metadata layer across clouds and on-premises environments.
Get started in minutes: Connect to storage and analytics environments in minutes and enhance trust in data with built-in governance, security, and automation.
Reduce the cost of your data warehouse by up to 50% through workload optimization: Optimize costly data warehouse workloads across multiple query engines and storage tiers, pairing the right workload with the right engine.
