OUR FIRST PRODUCT
The HD Hyperscale Datastore
HD is a purpose-built, pure storage engine for Hyperscale Datasets. By decoupling storage from processing and re-architecting how data is physically stored and accessed, HD eliminates the bottlenecks that plague legacy systems.
A Fundamentally Different Approach
HD's "post-file era" architecture is the key to its transformative performance. We bypass the file and file system entirely, not just manage it ourselves.
Instead of files, HD stores records in a simple binary array on block storage, eliminating file system overhead. This allows HD to apply simple and high-speed filters directly at the hardware level, in parallel, using advanced vector processing built into every modern CPU/GPU/FPGA. The costly, multi-round SerDes process is completely avoided. HD reads only the bytes it needs and streams them directly to your application.
The Proof: 100x Performance, Up To 98% Less Cost
These numbers are not incremental improvements; they are the result of architectural transformation.
How We Achieve 100x Performance
Performance is gained by eliminating work. Legacy systems waste up to 90% of their compute cycles on SerDes—work that HD's architecture makes obsolete. By filtering at the hardware level and bypassing the file system, we avoid the CPU and memory bottlenecks of deserialization. We stream only the requested records at the full sequential read speed of the underlying NVMe drives, resulting in a radical performance increase.
How We Achieve A 98% Cost Reduction
Cost is a direct function of compute resource consumption. By removing the massive CPU and memory overhead of SerDes, HD requires a fraction of the compute resources to perform the same task. This means fewer servers and VMs, smaller cluster sizes, and a dramatically lower OPEX/CAPEX. Furthermore, by enabling a "Data-Centric" model, you store the raw data once, eliminating the storage costs and engineering overhead of maintaining multiple, redundant "application-centric" rollups.
Built for Builders: The HD SDK
The most innovative work in your organization is done in custom code. The primary interface to HD is a powerful SDK that plugs directly into the modern developer's workflow.
Restrictive interfaces like SQL and complex ORMs are not just a tax on productivity but a drag on your services performance as data is mutated from model to model before you actually make use of it. The HD SDK is designed to accelerate developer velocity by delivering a direct, high-speed stream of pre-filtered data in a format native to their language, such as a Python DataFrame or a JSON object. This allows your teams to integrate raw, high-fidelity data into their microservices and AI models without the performance penalties or complex data engineering pipelines that slow them down.