Speedata raises $44M Series B: can its APU outpace Nvidia in big data?

Speedata, a Tel Aviv-based startup, has secured $44 million in Series B funding to further develop its analytics processing unit (APU), which is purpose-built to accelerate big data analytics and AI workloads.

Unlike general-purpose processors or GPUs designed for other tasks, Speedata's APU is engineered specifically for data processing. According to the company, a single APU can replace entire racks of servers, delivering significantly enhanced performance.

"But these are either general-purpose processors or processors designed for other workloads, not chips built from the ground up for data analytics. Our APU is purpose-built for data processing and a single APU can replace racks of servers, delivering dramatically better performance."

In a notable demonstration, Speedata's APU completed a pharmaceutical data workload in just 19 minutes, compared to 90 hours on a non-specialized processing unit — a 280x speed improvement.

The startup aims to establish its APU as the standard processor for data analytics, similar to how GPUs became the default for AI training.

"We aim at becoming the standard processor for data processing — just as GPUs became the default for AI training, we want APUs to be the default for data analytics across every database and analytics platform," said Gelvan, Speedata's representative.

This funding round positions Speedata to challenge established players like Nvidia by offering specialized hardware that could revolutionize big data processing efficiency and speed.

Speedata, a Tel Aviv startup, raised $44 million in Series B funding to advance its analytics processing unit (APU) designed to accelerate big data and AI workloads. The APU claims a 280x speed improvement over non-specialized processors, aiming to rival Nvidia in data analytics performance.