IBM Netezza Performance Server Alternatives (January 2026)

IBM Netezza Performance Server is a data warehouse for demanding hybrid-cloud environments available as SaaS and for self-hosting through IBM Cloud Pak for Data System.

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1.
IBM Db2
https://www.ib
.com/db2/

IBM Db2 is the database to run your mission-critical workloads. Power low-latency transactions and real-time analytics across any cloud, hybrid or on-prem.

3.
IBM Informix
https://www.ib
.com/products/informix/

IBM Informix is an embeddable, high-performance database for integrating SQL, NoSQL, JSON, time-series and spatial data. It is available as a managed service on IBM Cloud, as standalone software, and within IBM Cloud Pak for Data.

4.
Cloud Data Warehouse - Amazon Redshift - AWS
https://aws.amazo
.com/redshift/

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data.

5.
IBM Cloud Pak for Data
https://www.ib
.com/products/cloud-pak-for-data/

IBM Cloud Pak for Data is a modular set of integrated software components for data analysis, organization and management.

6.
IBM Storage Suite for IBM Cloud Paks
https://www.ib
.com/products/storage-suite-for-ibm-cloud-paks/

IBM Storage Suite for IBM Cloud Paks delivers secure persistent storage resources for your Kubernetes and Red Hat OpenShift container environments.

7.
Power servers | IBM
https://www.ib
.com/power/

IBM Power servers accelerate big data insights and hybrid cloud deployment with an open server ecosystem.

8.
IBM InfoSphere Master Data Management
https://www.ib
.com/products/ibm-infosphere-master-data-management/

IBM InfoSphere Master Data Management is master data management software to consolidate and govern business data. It is available for self-hosting, as managed SaaS, and in IBM Cloud Pak for Data.

9.
IBM Knowledge Catalog
https://www.ib
.com/products/knowledge-catalog/

IBM Knowledge Catalog is software to manage and curate data, knowledge assets and their relationships. It is available as managed SaaS or within IBM Cloud Pak for Data.