Applications that once worked with bounded datasets now need access to massive, constantly growing volumes of operational and analytical data. At the same time, many enterprises still need control over where that data lives, how it is governed and what infrastructure costs look like over time.
That is where SingleStore and HPE Alletra Storage MP X10000 come together.
Recent testing showed that SingleStore performs well when deployed with HPE Alletra Storage MP X10000, giving enterprises another option for scaling AI and analytics applications outside traditional cloud-only environments.
A Practical Path for Enterprise AI
Much of the industry conversation assumes that AI workloads belong in hyperscale clouds. For many companies, that is the right choice.
But it is not the only choice.
Enterprises building the next generation of AI applications often need:
Fast transactional performance
Real-time analytics on fresh data
Scalable storage for growing datasets
Predictable infrastructure costs
Greater control over where data lives
That is where modern disaggregated architectures come into play.
How the Architecture Works
SingleStore separates compute from storage through its Unlimited Storage architecture, allowing organizations to scale large datasets without scaling compute resources at the same rate.
HPE Alletra Storage MP X10000 provides a high-performance, S3-compatible object storage platform that can serve as the storage layer for those deployments.
Together, the two technologies give enterprises a way to run modern HTAP workloads while keeping data in environments they control. No mystery, no elaborate Rube Goldberg machine of data movement — just compute where you need it and storage that can keep up.
The value proposition is straightforward:
Store more data without constantly adding database compute
Run transactional and analytical workloads in a single platform
Support AI and analytics initiatives on self-managed infrastructure
Avoid unnecessary data movement between systems
Preserve deployment flexibility as AI applications scale
Performance
For OLTP workloads using the TPC-C benchmark, SingleStore running on HPE Alletra Storage MP X10000 delivered performance essentially on par with a comparable public cloud deployment, achieving 12,589 tpmC versus 12,545 tpmC in the cloud.
For analytical workloads using the TPC-H benchmark on a 10 TB dataset, the results were even more notable. HPE reported that the X10000 configuration outperformed comparable public cloud results by more than 30% in both cold and warm query runs.
In other words, enterprises evaluating this architecture do not have to assume that keeping data closer to home means settling for less performance.
More Choice for Enterprise AI Infrastructure
This is not about replacing the cloud. It is about giving enterprises more options.
Many organizations will continue to run SingleStore in managed cloud environments. Others may choose hybrid deployments. Some will prefer to keep critical workloads on infrastructure they manage directly.
SingleStore supports all of those approaches.
As AI applications become more central to the business, infrastructure decisions are becoming less about where the industry says data should live and more about what works best for each organization. The future probably belongs to a mix of approaches anyway — a patchwork of clouds, data centers, edge systems and whatever comes next.
For enterprises looking to scale the next generation of AI applications without committing to an all-cloud approach, SingleStore and HPE Alletra Storage MP X10000 represent another viable option for building scalable AI and analytics platforms without giving up performance or control.
