Data Analytics Acceleration

Acceleration Built for AI Era
Faster. Higher Scale. More Efficient.

Optimizing query processing at scale to efficiently meet the demands of modern AI / machine-driven insights and decision-making.

NeuroBlade Deployment Options

NeuroBlade Accelerator is available in cloud instances or as a PCIe card for seamless on-premises integration, offering flexibility for data analytics acceleration in the AI era, where large amounts of data are stored and utilized for ML and inference workloads. Accessible via the robust DAXL (Data Analytics Acceleration Library)

API, NeuroBlade integrates with open-source query engines like Apache Spark, Presto, and ClickHouse. Whether your organization deploys workloads in the cloud, on-premises, or hybrid, NeuroBlade accelerates data analytics, enhances performance, reduces TCO, and delivers faster value.

QPH Per Number of Streams

TPC-H (SF=1000)

NeuroBlade’s acceleration technology is built for real-world analytics, optimizing multi-stream workloads. Benchmarks show unaccelerated solutions (Presto/Presto-Velox) struggle to scale QPH as streams increase, while NeuroBlade-accelerated setups deliver significantly higher QPH. This efficiency enables superior performance and reduced TCO with a smaller cluster footprint.

Test Setup
TPC-H SF=1TB (scale factor)
2 Physical servers
8 worker nodes + 1 Coordinator
16 vCores per worker
1 Accelerator per server (accelerated setup only)

Benefits

Data Analytics Acceleration Library (DAXL)

DAXL API integrates seamlessly with popular open-source query engines for analytical data processing like Apache Spark, Presto, and ClickHouse, enabling easy adoption with existing workflows.

Performance Comparison TPC-H

Faster Queries with NeuroBlade
Scale Factor= 1000

Available Integration References

Note: Contact us for additional reference integration
with other open-source query engines

Documentation

DAXL SDK 🔒 Get Access
Hardware Guide 🔒 Get Access
NeuroBlade Big Data Analytics White Paper Download
NeuroBlade TCO White Paper Download

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Technical Resources

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