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Handling data at the network edge is not a new idea, but it is becoming more important as organisations grapple with growing data volumes and the need to process information quickly. Computational storage is, however, a relatively new way to tackle that challenge. A key driver here is that conventional IT systems, with separate compute, networking and storage components, come with inherent bottlenecks. One option is hyper-converged infrastructure (HCI), where processing, storage and networking are integrated into nodes that can be built into clusters. Computational storage goes a step further, and puts processing onto the storage sub-system itself. This, its advocates say, offers far greater efficiency when data growth comes from the proliferation of sensors and the internet of things (IoT), or needs rapid processing for artificial intelligence (AI) and machine learning (ML) use cases. However, the technology is still relatively immature, with only a handful of suppliers offering computational storage hardware, although a larger...