ScaleFlux Computational Storage supercharges big data analytics infrastructure and is driving a new paradigm in accelerating time-to-insight.

By parallelizing queries across Computational Storage Drives instead of bottlenecking at a central processing host, ScaleFlux is knocking down barriers to consistent query response despite data sets quickly growing into the Exabyte range and beyond.

ScaleFlux Computational Storage is optimized with inline data pre-processing that is critical to keep throughput starved GPUs fed directly, versus traditional centralized compute architectures that impede the flow of data.

With line-rate data path compression and decompression, and programmable data scanning and filtering algorithms natively on every Computational Storage Drive, ScaleFlux is the foundation for AI infrastructure that enables real-time training and learning models.

ScaleFlux Computational Storage enables low-latency Flash deployments in 5G/edge environments that demand fast response to a huge influx of IOT data processing versus traversing to compute resources deeper in the cloud.

By transparently minimizing the storage footprint and offering programmable data processing algorithms on each Computational Storage Drive, ScaleFlux is reducing the storage capacity and power footprint for ultra-low latency storage applications as they emerge at the edge.

ScaleFlux Computational Storage offers cost-effective Flash storage for content delivery systems that are tasked with pre-processing high-throughput streaming data on its way to end users.

Through parallelization of connection based security protocols or the implementation of real-time error correction, ScaleFlux provides a programmable Flash Storage solution that scales content delivery systems efficiently and cost-effectively.