IBM announced a major upgrade to the Db2 database that is designed to enable enterprises to infuse AI and data science into their database management processes to more easily build AI into applications and gain greater insights from their data.
Among the many enhancements in Db2 version 11.5, is built-in support for data science development. Through a series of newly-available drivers for multiple open source programming languages and frameworks, it will now be easier for developers to analyze and build machine learning models into applications using Db2. The enhancements are designed to help Db2 developers more easily write applications that require less management, are more resilient to outages, and help improve productivity.
"Today, expectations for the database are higher," said Prasun Mahapatra, senior database administrator at Micro Focus, and a Db2 user. "Databases must be smarter. Building out Db2 as the new AI database will enable users to optimize everything from the usage of data structures, memory and disk, to the most complex queries. And the access to such an extensive set of Jupyter Notebooks enables people to kickstart their Db2 development."
Also new with Db2 11.5 is the Augmented Data Explorer, a new natural language querying feature that is designed to give developers a traditional search engine-like experience. Users can pose questions to Db2 and receive results in data visualizations and summaries written in natural language, for easy understanding.
In addition to these advances, Db2 users and developers will be able to take advantage of the new capabilities in IBM's Data Virtualization technology – already available with IBM Cloud Private for Data. Data Virtualization is designed to enable users to easily search across diverse data sources.
With it, developers and data engineers can focus on development, minimizing time spent on extract, transform, and load (ETL) processes that are associated with moving data. Db2 now also includes BlockChain support that helps application developers pull data directly from a BlockChain and combine that data with other data sources for analytics or dashboards.
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