Chip startup Speedata, a competitor of Nvidia, secures $44 million in Series B funding

Speedata raises $44M in Series B funding to compete with Nvidia in data analytics processing.

: Speedata, a startup from Tel Aviv, raised $44 million in Series B funding to further develop its unique analytics processing unit (APU) aimed at boosting big data analytics and AI workloads. The funding round was supported by existing investors such as Walden Catalyst Ventures, 83North, Koch Disruptive Technologies, Pitango First, and Viola Ventures, with Lip-Bu Tan and Eyal Waldman also investing. Speedata's APU is designed to replace traditional processors and can significantly outperform non-specialized units by being more efficient for data analytics tasks. Despite its focus on Apache Spark workloads, the company plans to support major data platforms, showcasing its APU as a revolutionary product.

Speedata, a Tel Aviv-based startup, announced raising $44 million in Series B funding to boost its technology that aims to revolutionize data analytics processing. This brings Speedata's total funding to $114 million. The innovative analytics processing unit (APU) developed by Speedata is designed to handle big data analytics and AI workloads better than traditional processors. Unlike GPUs which are general-purpose, Speedata's APUs are custom-built from the ground up specifically for data analytics.

The Series B funding round saw participation from several existing investors like Walden Catalyst Ventures, 83North, Koch Disruptive Technologies, Pitango First, and Viola Ventures. Strategic investments also came from industry leaders such as Lip-Bu Tan, CEO of Intel and Managing Partner at Walden Catalyst Ventures, and Eyal Waldman, Co-Founder and former CEO of Mellanox Technologies. This reflects significant confidence in Speedata's potential to transform data processing in industries relying heavily on analytics.

CEO Adi Gelvan emphasized the limitations of existing processors, underscoring that Speedata's APU can replace multiple servers with a single unit to deliver dramatically better performance. The APU technology focuses on overcoming specific bottlenecks in analytics at the computing level. One notable instance highlighted by Gelvan was completing a pharmaceutical workload in 19 minutes, compared to 90 hours on traditional systems, indicating a 280x speed improvement.

Founded in 2019 by six individuals deeply familiar with Coarse-Grained Reconfigurable Architecture (CGRA) technology, Speedata aims to establish its APU as the standard processor in data analytics, similar to how GPUs have become crucial in AI training. Originally targeting Apache Spark workloads, Speedata intends to broaden its support to every major data analytics platform as part of its future roadmap. Their approach has caught the attention of several large companies already testing their APU, although these firms remain unnamed ahead of an official product launch.

Speedata plans its first public showcasing of the APU at the upcoming Databricks’ Data & AI Summit. Despite initially designing and manufacturing the APU in late 2024, the company has transitioned from testing on field-programmable gate arrays (FPGAs) to having functional hardware ready for market. The startup is now poised to scale up operations amid a growing anticipation from enterprise customers eagerly awaiting the new technology.

Sources: Speedata, TechCrunch

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