Watsonx.data is an open, hybrid, and governed data store that helps enterprises scale analytics and AI workloads. It is built on an open lakehouse architecture, supported by querying, governance, and open data formats to access and share data.
Features of Watsonx.data :
- Fit-for-purpose query engines: Watsonx.data supports multiple query engines, including Presto and Spark, to provide fast, reliable, and efficient processing of big data at scale.
- Built-in governance, security, and automation: It includes built-in unified governance capabilities to help ensure enterprise compliance and security. It also supports integration with existing governance solutions.
- Vendor-agnostic data formats: It supports vendor-agnostic open formats for analytic data sets, such as Apache Iceberg table format and Apache Hive metastore. This allows different engines to access and share the same data at the same time.
- Cost-effective, simple object storage: It can store large volumes of data in low-cost object storage and share it through an open table format built for high-performance analytics.
- Hybrid cloud deployments: It can be deployed seamlessly across any cloud or on-premises environment in minutes with workload portability through Red Hat OpenShift.
Benefits:
- Scale analytics and AI workloads: Watsonx.data can help enterprises scale analytics and AI workloads by providing a unified platform for data storage, processing, and governance.
- Reduce data warehouse costs: It can help enterprises reduce data warehouse costs by optimizing workloads across multiple query engines and storage tiers.
- Improve data governance and security: It includes built-in governance and security capabilities to help enterprises ensure compliance and protect their data.
- Increase agility and flexibility: It’s hybrid cloud deployment capabilities give enterprises the flexibility to deploy their data workloads wherever they need them.
Use cases:
- Data warehousing: Watsonx.data can be used as a data warehouse to store and analyze large volumes of data.
- Data lake modernization: It can be used to modernize data lakes by adding data warehouse-like performance, security, and governance.
- Machine learning: It can be used to train and deploy machine learning models at scale.
- Business intelligence: It can be used to power business intelligence applications that provide insights into enterprise data.
- Real-time analytics: It can be used to power real-time analytics applications that provide insights into data as it is generated.
Overall, Watsonx.data is a powerful and versatile data store that can be used for a wide variety of data workloads. It is a good choice for enterprises that need to scale analytics and AI workloads, reduce data warehouse costs, and improve data governance and security.
