IBM is introducing a variety of AI tools to IBM SQL Data Insights Pro (SQL DI Pro), generally available as of March 2026, offering semantic search, similarity discovery, anomaly detection, and unified analysis of structured and unstructured data in Db2 for z/OS.
In SQL DI Pro, AI moves to Db2, thereby reducing risks in areas such as privacy, compliance, and data inconsistency that arise when customers are required to move data to other analytical frameworks, IBM said.
From a research perspective, SQL DI Pro represents an initial pioneering product of AI and data systems integration, opening the door to further AI systems integration research.
This technology was ideated and prototyped by the IBM Research team. It extends traditional SQL from syntax-based querying to AI-driven pattern discovery, enabling developers and data analysts to uncover insights from both structured and unstructured data that were previously difficult or impossible to access, IBM said.
By embedding advanced semantic analysis directly within Db2 for z/OS, SQL DI Pro enables the following:
- Deeper and more intuitive data understanding
- Reduced need for external data processing pipelines
- Lower operational cost and complexity
- Easier compliance with data sovereignty and governance requirements
SQL DI Pro builds on the foundation established by SQL Data Insights (SQL DI), also developed by the IBM Research team.
SQL DI introduced the concept of embedding structured relational data into dense vector representations, enabling similarity-based operations such as clustering and entity comparison directly within Db2.
By transforming rows into vectors in a latent space, SQL DI allowed relational data to be analyzed beyond exact-match predicates, supporting approximate reasoning over business data entities, IBM said.
SQL DI Pro significantly extends this foundation to fully capture semantic meaning in unstructured data. SQL DI Pro incorporates modern encoder models from IBM to generate high-quality embeddings for columns containing long unstructured text. This enables semantic understanding that surpasses traditional structured data analysis.
This unified approach allows users to perform end-to-end AI-driven discovery across diverse data types in Db2 for z/OS, while applying the most suitable models for each data modality, said IBM.
SQL DI Pro introduces four built-in SQL functions to support semantic analysis. These functions can be embedded into SQL statements for unified data processing.
SQL DI Pro also includes an incremental retraining algorithm that eliminates the need for costly full retraining of database embeddings when new data is introduced. This approach enables embeddings to be updated as new data arrives or existing data changes, significantly reducing compute and processing overhead compared to full retraining.
SQL DI Pro accelerates both embedding generation and model inference by leveraging the on-chip AI capabilities of IBM Z Telum processors, in conjunction with the IBM Z Deep Learning Compiler (zDLC)—a compiler stack developed by IBM Research to optimize deep learning workloads for z/Architecture.
This acceleration is central to making semantic query processing practical inside Db2 for z/OS. Operations such as embedding generation, similarity scoring, clustering, and anomaly detection can be computationally intensive, especially when applied to large enterprise datasets.
By optimizing these workloads for IBM Z AI acceleration, SQL DI Pro brings AI closer to mission-critical data while reducing the need to move sensitive information into external analytical environments, according to IBM.
For more information about this news, visit www.ibm.com.