Speedata Launches with $70M to Revolutionize Big Data Analytics

The Rise of Specialized Chips in Data Centers

Data centers are increasingly adopting specialized chips designed for specific workloads, shifting away from traditional CPUs. This transition involves integrating GPUs and other accelerator types to manage the demands of complex and resource-intensive computations.

Speedata, a startup developing a processor focused on big data analytics, has emerged from stealth mode, announcing $70 million in funding. This investment will facilitate continued product development and the initiation of its initial commercial engagements.

Speedata's Innovation and Funding

In a landscape characterized by a growing number of purpose-built chipsets, Speedata asserts it has created “the world’s first dedicated processor for optimizing cloud-based database and analytic workloads.”

CEO and co-founder Jonathan Friedmann revealed that Speedata’s technology has demonstrated a performance increase of approximately two orders of magnitude during pilot programs with major companies, including hardware manufacturers, cloud providers, and end-users.

Speedata, being a fabless chip startup, will now concentrate on chip production and securing commercial agreements, potentially with companies involved in the pilot testing phase.

Funding Details and Company Background

Founded in 2019, Speedata’s funding is structured in two phases. An initial $15 million seed round, led by Viola and Pitango, preceded a recent $55 million Series A round.

The Series A funding was spearheaded by Walden Catalyst Ventures, 83North, and Koch Disruptive Technologies (KDT), with participation from Pitango and Viola, as well as Eyal Waldman, co-founder and former CEO of Mellanox Technologies.

The founding team – comprising Jonathan Friedmann, Dan Charash, Rafi Shalom, Itai Incze, Yoav Etsion, and Dani Voitsechov – possesses substantial experience in both academia and the chip industry, boasting numerous successful exits and significant patents.

Addressing the Challenges of Big Data Analytics

Speedata’s focus on big data analytics stems from the inherent difficulties in resolving data fragmentation across various sources. The company has not yet disclosed the specifics of its breakthrough.

Furthermore, big data analytics represents a substantial workload within data centers, making it a prime candidate for dedicated processor optimization, surpassing the capabilities of current CPUs and FPGAs.

While distinct from AI workload processing – a domain currently led by Nvidia – Nvidia could become a competitor as it broadens its technological scope.

The Growing Importance of Data Analytics

Speedata recognizes the urgency of capitalizing on this opportunity, as the bottleneck in data analytics is only recently becoming apparent.

The volume of data generated within enterprises is experiencing exponential growth. Speedata cites IDC research indicating that the data created in the next three years will exceed that of the previous three decades.

However, the advancement of analytics processing has slowed due to this increasing data volume, necessitating innovative processor solutions.

Friedmann emphasizes that addressing this challenge requires a multidisciplinary approach, encompassing networking improvements and a thorough understanding of deep learning software.

Market Opportunity and Future Outlook

Speedata views this as a unique market opportunity, estimating that analytics account for approximately 50% of data center expenses, representing a significant market size.

Enhanced big data analytics promises deeper insights with applications in fields like medical research, financial services, cybersecurity, and autonomous systems.

The big data analytics market is projected to reach $70 billion by 2025, driving demand for improved hardware and services.

“Datacenter analytics are being completely transformed, and accelerated processors are set to play a substantial role in this revolution,” stated Waldman. “Speedata’s unique APU will transform database computing, much like NVIDIA’s GPU revolutionized the AI space.”