Lenovo and WEKA collaborate for hybrid cloud data management solutions

Lenovo and WEKA announced a new global agreement focused on offering solutions for next-generation data management architectures and performance-intensive workloads for delivery in more than 160 markets worldwide. These comprehensive solutions will accelerate artificial intelligence (AI) and analytics for high-performance workloads, including finance, genomics, life science, media and entertainment applications around the world by speeding time to insights while reducing associated costs.

The performance and scalability requirements of next-generation workloads must be met by modern data management systems, which also need to be dependable and secure. Lenovo will combine WEKA’s ultra-high-performance, hybrid cloud data platform software with its leading Lenovo ThinkSystem servers to deliver an incredibly potent, high-performance, and scalable data management solution for AI and data analytics as part of the company’s expanding data management investments and momentum.

The ThinkSystem SDS Ready Nodes, combined with the WEKA Data Platform software, will offer customers an extensive range of configuration options, including the latest Intel and AMD processors, NVIDIA GPUs, NVMe drives, and fast networking selections. These validated systems can be easily deployed for scale-out workloads, streamlining deployment and minimizing risk, resulting in faster production times.

Dr Roberto Fabbretti, PhD, Director of the Computing and Research Support Division at the University of Lausanne said “We use Lenovo ThinkSystem servers with WEKA Data Platform software as the foundation for our high-performance computing environment for the processing of sensitive data.”

Fabbretti said “The processing of medical or sensitive data is subject to increasingly stringent legal and technical constraints. We find these two partners to be particularly attentive to these issues and are among the few providers of products that can combine very high performance with strong data security. These types of platforms form the powerful, scalable, reliable, and secure data infrastructure that underpins SENSA, our next-generation data processing and analytics platform, which is accelerating biomedical research and discovery throughout Switzerland.”

The combined Lenovo and WEKA solution is designed to offer performance and leadership standard uptime while simplifying scale. Enterprises can use hybrid on-premise and cloud resources for cloud bursting and scalability if they have WEKA-integrated ThinkSystem SDS Ready Nodes.

Kamran Amini, Vice President and General Manager of Server & Storage, Lenovo Infrastructure Solutions Group said “As a global top five storage provider, Lenovo is committed to empowering intelligent transformation and accelerating the new era of IT through deep collaboration with the new scalable data management solutions.”

Amini said “This partnership is an important next step in enabling more customers to seamlessly leverage AI, analytics, and machine learning (ML) to advance their businesses and help solve humanity’s greatest challenges.”

Jonathan Martin, President at WEKA said “Lenovo’s industry-leading servers perfectly complement WEKA’s high-performance data platform software. Together, they deliver the robust, highly scalable, performant, and secure foundation that performance-intensive workloads require.”

Martin said “For organizations looking to innovate or power research and discovery with AI, ML, and HPC, this solution promises to be transformative. We are thrilled to be working with Lenovo to deliver it to customers in over 160 countries worldwide.”

Lenovo’s ThinkSystem SDS Ready Node solutions, which have been tested, optimized, and certified with the WEKA Data Platform, include the SR630 V2, SR635 V2, SR650 V2, and SR655 V2 models. Customers can purchase WEKA software licenses through Lenovo and quickly deploy these validated Ready Node systems for all scale-out workloads, simplifying deployment, minimizing risk, and resulting in faster production times.