In today’s data and AI-driven world, organizations are generating vast amounts of data from various sources. The ability to extract value from AI initiatives relies heavily on the availability and quality of an enterprise’s underlying data. In order to unlock the full potential of data for AI, organizations must be able to effectively navigate their complex IT landscapes across the hybrid cloud.  

At this year’s IBM Think conference in Boston, we announced the new capabilities of IBM, an open data lakehouse that enables enterprises to unlock value in their existing data by connecting to existing storage and analytical environments, regardless of where their data resides. It also allows them to prepare their data for AI use cases and cost-optimize workloads with multiple fit-for-purpose query engines and low-cost object storage.  

From mobile banking applications to connected cars, clients rely on IBM® databases to store and analyze their most critical data across the hybrid cloud, powering applications and analytics that operate their business every single day. IBM Netezza® Performance Server is a cloud-native enterprise data warehouse designed to operationalize deep analytics, business intelligence and machine-learning (ML) workloads by making data unified, accessible and scalable, anywhere. Today, we are excited to announce the general availability of both IBM Netezza on-premises (Cloud Pak® for Data System) and IBM Netezza SaaS integrations with™.  

Let’s explore how the integration of Netezza with can now help clients modernize their data management platform to drive actionable insights with other third party data and applications for generative AI.  

Unifying data for AI 

Traditional data warehousing approaches often require complex ETL (Extract, Transform, Load) processes, which can be time-consuming and costly. With Netezza and, you can unify data for AI across the hybrid cloud without the need for ETL. This is achieved through a shared metadata layer, open table formats, and cost- effective cloud object storage. With new support for open formats such as Parquet and Apache Iceberg, Netezza empowers data engineers, data scientists and data analysts to run complex workloads without additional ETL or data movement over cloud object storage. 

This integration enables Netezza on-premise customers to read and write Apache Iceberg tables stored on cost effective S3 compatible object storage either on-premise or in cloud along with joining Netezza native tables (hot/warm data) and in-frequently accessed stored in Iceberg tables (cold data).  Shared metadata, storage, and open table Iceberg data formats facilitate data access and sharing across multiple Netezza instances running on premises and/or Netezza on Cloud. 

With greater access to’s Presto and Spark open-source query engines, this integration approach also allows Netezza customers to optimizes workloads for price-performance, pairing the right workload, with the right engine, for the right cost. brings new generative AI capabilities for Netezza customers’s built-in generative AI capabilities powered by the semantic layer as part of IBM Knowledge Catalog enable Netezza customers to prepare and simplify data for new AI applications using natural language. This reduces the complexity of data preparation and enables faster time-to-insight. also announced the availability of their integrated vector database, based on open source Milvus. Now, Netezza clients can unify, curate and prepare vectorized embeddings for their generative AI applications at scale across their trusted, governed data within This helps enhance the relevance and precision of AI outputs, including chatbots, personalized recommendation systems and image similarity search applications. 

Deploy your Netezza data warehouse with integration anywhere  

Netezza customers running workloads both on-premises with Netezza Cloud Pak for Data System as well as Netezza SaaS customers running on AWS and Azure can now leverage this integration with For on-premises Netezza clients looking to move to a hybrid cloud architecture to achieve greater flexibility and scale for AI, Netezza makes it easy to modernize to hybrid and fully managed deployments on AWS and Azure with like-for-like compatibility.  

“Sicoob enables its credit unions to prosper financially and socially through sustainable financial solutions that are in line with the cooperative spirit. The transition to a cloud-based solution, with IBM Netezza® SaaS on AWS, was straightforward and shows that it is possible to achieve greater operational efficiency in a secure and updated cloud environment with predictable costs.It is equally important to highlight that, in a business context where business decisions are increasingly driven by data and analytical processing is a vital component to business success, the selection of IBM as a business partner provided the reliability and competence of execution that the corporation expected. We are now looking at how to leverage this infrastructure for new analytics and AI use cases, and are excited by the possibilities of the IBM Watsonx platform that Netezza integrates with.”  —Antonio Vilaça Júnior, Sicoob CIO

Getting started  

Netezza on-premises and Netezza SaaS integration with provides a powerful solution for scaling analytics and AI across the hybrid cloud. With zero ETL required, you can unify data for AI, access and share data across the hybrid cloud, and store and share data for AI using open formats and low-cost object storage. By leveraging built-in generative AI capabilities and native integrations, you can simplify data preparation and accelerate your AI journey. 

Try Netezza for free

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