Technical architects, data platform engineers, and infrastructure leads evaluating storage platforms for on-premises or hybrid data lakehouse deployments where GPU efficiency, AI workload support, and scalability without architectural ceilings are requirements.
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Legacy scale-up and scale-out storage platforms impose architectural constraints — S3 gateway overhead, controller-bound performance, and vendor-published scaling ceilings — that become acute and costly as lakehouse and AI workload demands grow.
Multi-protocol platforms avoid hard scaling limits but introduce protocol contention that degrades S3 performance unpredictably, requiring operational complexity that erodes the consolidation value proposition.
AIStor Tables collapses the traditional 4-layer Iceberg stack (query engine, REST catalog, PostgreSQL metastore, object storage) to 2 layers by embedding the Iceberg REST catalog API directly into the storage platform.
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