As organizations become better at managing and using a wider range of data, they will increasingly adopt and leverage AI. According to Rob Thomas, General Manager of IBM Data and AI, organizations cannot have effective AI without a robust IA (Information Architecture). One of the pillars of any IA is data management.
In this new data age, ai database open source are no longer considered traditional systems of record or data storage. These days, expectations are higher. Databases must be smarter. They should understand what is being searched for and find the most relevant information while using the most optimal way to locate data. As organizations try to become more agile, they want a faster, easier way to conduct analytics across these hybrid data stores without the costly and time-consuming effort of duplicating, duplicating, transforming, or moving data Say, no more extracting, transforming, loading data (ETL). They must also be self-managing and self-healing, reducing maintenance overhead.
In other words, what we need is an AI-infused database.

That's the vision for IBM Db2; to be the AI database that can help power today's cognitive applications. IBM Hybrid Data Management (HDM), built on the Db2 Common SQL Engine, provides a platform to manage all data types from all sources and targets.
Because of the software's high reliability, resiliency, security, and more, thousands of organizations rely on IBM Hybrid Data Management and Db2—the leader in Online Transaction Processing (OLTP), Online Analytical Processing (OLAP) and Big Data—to run mission critical applications. With this new vision, Db2, a core component of the hybrid data management platform, will also help customers accelerate their AI application development while automating parts of data management.

We're positioning IBM Db2 as the database of choice for AI application developers and data scientists. For example, starting today, IBM Db2 provides drivers for popular data science languages and frameworks, including Go, Ruby, Python, PHP, Java, Node.js, Sequelize, and Jupyter Notebook, enabling developers and data scientists to build AI application data for the first time. These drivers are now available on GitHub.