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Accelerate Analytics to the Speed of Data

Boost Apache Spark and Presto price-performance 100x at the hardware layer, where it matters most

RE-CAPTURE LOST BUSINESS VALUE BY PRIORITIZING CAPACITY FOR YOUR MOST DATA-INTENSIVE WORKLOADS

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Data continues to explode and is even accelerating growth. But much goes unused, and most data teams are underutilized. The limitations of traditional CPUs continue to lead to missed SLAs and prevent potentially transformational analytics projects from getting kicked off at all.

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While analytics represent the largest, most resource-intensive workload in the data center, modern enterprises need novel domain-specific processors that can deliver performance speed, scale, and efficiency starting at the hardware layer.

THE FIRST PROCESSOR DESIGNED FOR ANALYTICS

Speedata’s Analytics Processing Unit (APU) is the only processor architected specifically to accelerate database analytics, still the largest and most expensive workload in the data center. The APU's orders-of-magnitude better price-performance ensures data engineers can refresh and expand the scope of their data, essential to long-running analytics and pre-processing data for AI.

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Price-Performance Improvement Factor for TPC-DS

100x FASTER PERFORMANCE AND 90% COST SAVINGS

Speedata’s early adopters have already seen an average of 50x better performance over CPUs for critical Spark workloads, with a path to 100x improvement. And head-to-head tests against GPUs have yielded an average 91% capital reduction for the Speedata APU, plus an expected 94% space savings and 86% power savings.

WHY SPEEDATA APU?

Boost top line

Accelerate 100x faster time to insight

Easily answer previously impossible questions

Pre-process data to unlock value from AI workloads

Lower costs

Process more data with a fraction of the servers

Cut data center footprint and energy costs up to 95%

Eliminate opportunity cost of biz-critical projects 

Increase productivity

Turn long-running jobs into interactive workflows

Rapidly test new ideas, expand, and refresh data

Unburden infra and IT teams from hardware maintenance

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