Businesses encounter significant challenges when getting data ready for artificial intelligence (AI) applications. Data silos, duplication, and concerns about data quality create a complex environment for organizations to navigate. Additionally, traditional database management tasks like backups, upgrades, and routine maintenance consume valuable time and resources, hindering innovation. These obstacles underscore the importance of a flexible, cloud-native infrastructure that can address these issues and scale according to AI workload demands, ultimately enhancing business outcomes.
To address these challenges, IBM’s range of SaaS database solutions on Amazon Web Services (AWS) enables enterprises to scale applications, analytics, and AI across the hybrid cloud landscape. By unifying and sharing a single copy of data and metadata across IBM® watsonx.data™, IBM® Db2®, IBM® Db2® Warehouse, and IBM® Netezza®, using native integrations and supporting open formats, organizations can optimize analytics for the best price-performance. Native integrations with IBM’s data fabric architecture on AWS establish a reliable data foundation, facilitating the acceleration and scaling of AI across the hybrid cloud.
IBM and AWS have partnered to accelerate customers’ cloud-based data modernization strategies. By leveraging IBM’s decades of database expertise in performance and combining it with AWS’s scalability, security, and governance features, customers can achieve enhanced flexibility, agility, and cost efficiency in the cloud. Transitioning existing IBM on-premises database customers to AWS is seamless, offering risk-free, like-for-like upgrades and enabling customers to modernize their infrastructure at their own pace.
In late 2023, IBM and AWS jointly announced the general availability of Amazon relational database service (RDS) for Db2, streamlining data management for AI workloads across hybrid cloud environments. IBM Consulting® and AWS have collaborated to help mutual clients operationalize and derive value from their data for generative AI (gen AI) use cases. These strategic initiatives assist companies in preparing their data for the next generation of applications, analytics, and AI workloads that will drive the modern economy.
IBM’s database portfolio available on AWS includes Amazon RDS for Db2, Db2 Warehouse SaaS on AWS, Netezza SaaS on AWS, and watsonx.data SaaS on AWS. These offerings provide secure, high-performance data management solutions that enable customers to scale analytics and AI workloads across their enterprise with trusted data. With features like cross-region disaster recovery, multi-availability zones, and advanced caching techniques, organizations can achieve faster performance and reduced storage costs while ensuring data security and compliance.
Customers can benefit from fully managed cloud deployments on AWS, seamless integration with IBM and AWS services, and the elimination of overhead, indexing, and tuning through automated maintenance. By choosing to modernize with IBM databases on AWS, customers can focus on their core tasks while AWS handles operations, automate administrative tasks, and achieve 100% workload compatibility for existing workloads in the cloud.
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