Oleg is the CEO of dxFeed, a market data and financial services firm. Over 20 years of experience in information technology and finance.
In a world where many of our online services are moving to the cloud, the data center space is experiencing a major shake-up. Existing providers are coming under pressure as hyperscalers like Amazon, Microsoft and Google enter the fray to bring low-latency elastic cloud infrastructure into traditional finance, entrenched in the on-premises and traditional datacenter build-ups.
In 2022, cloud infrastructure spending reached $60.5 billion, up more than 20% from the previous year, and is expected to grow to $93.7 billion in 2023. According to the International Energy Administration (IEA), data center energy consumption in 2022 accounted for around 1%-1.5% of global demand. Forecasts vary widely, but in my research, I found this figure is expected to rise between 3%-10% by 2030.
This shift also has significant consequences for market data services, my company’s niche. As the world continues to migrate to the cloud, with cloud-based infrastructure spending expected to surpass non-cloud spending this year, hyperscalers are also targeting the data provision world, making their direct connections to exchanges, offering full-scale market data infrastructures via the cloud.
Obstacles And Risks
There are some technical obstacles to this disruption. Providing a seamless flow of low-latency data from exchanges over the cloud has traditionally been more challenging than the existing approach of collocating bare metal servers on the premises of relevant venues.
The current limitations in delivering multicast traffic and the intolerance for packet loss in financial applications are both hurdles that the industry is currently striving to overcome. As headway is made and solutions emerge, the provision of high-quality, low-latency market data over the cloud is becoming increasingly feasible.
When it materializes, hyperscale providers entering the market data industry will pose an existential threat to many existing providers. These businesses may find it difficult to compete with the resources, capabilities and pricing power of these new hyperscale entrants, rendering current business models obsolete and necessitating rapid adaptation. While the traditional players in the field have accumulated a lot of know-how, specific expertise in the industry standards, protocols and domain knowledge, the hyperscale rapid build-up in the field paired with certain strategic mergers and acquisitions might turn the tables very quickly.
If history is anything to go by, in such a scenario, the industry could experience waves of M&A activity among its most successful players, who are likely to either be acquired by their competitors or band together, attempting to fend off the onslaught by merging. Other less successful players are likely to struggle in such an environment and ultimately be consigned to the history books.
Opportunities
The promise of low-latency market data in the cloud, coupled with unparalleled scalability and access, presents new opportunities for the entire ecosystem of market data vendors, exchanges and even market participants.
The shift could lead to an elastic data environment that can adapt to varying workloads, harnessing cloud processing power as needed, remaining globally available at all times and automatically scaling down when these resources are not required. Hyperscalers are also known for bringing prices down and making the services they offer much more widely available. Despite the ongoing process of market democratization and the revolution in market access, the world of market data can still be described as a collection of walled gardens. The coming revolution in cloud-based market data is sure to alter this situation, making high-quality market data available to a much larger percentage of the global population.
Another important aspect of this convergence is the synergy between market data and the availability of artificial intelligence (AI) at scale, which these same hyperscalers are also heavily involved in. The ability to apply AI tools to market data has the potential to revolutionize the market data industry by empowering market data vendors to offer proprietary AI-enhanced analytics, predictive modeling and real-time insights.
How To Survive Disruption
Competition from hyperscalers poses a completely new type of threat for incumbents, making survival strategies from the pre-hyperscaler era highly impractical. For instance, attempting to match the pricing power of these behemoths is an exercise in futility. Instead, I recommend the following:
Embrace Change
Change is the only certainty, which means that businesses locked into set business models or strategies will likely be the first to go. Every disruption comes with opportunities. Never forget that you are the specialist in your given field, and so are best positioned to spot where the next opportunity will present itself.
Collaborate
If you are open-minded and embrace change, there’s a good chance that you possess a much more thorough understanding of the field currently undergoing disruption than even those doing the disrupting. Explore partnerships and joint ventures, share what you know, offer solutions and in the process, gain access to new technologies and resources.
Differentiate
It’s critical that you define the unique advantages and value propositions that your business possesses. Offer specialized services and tailored solutions that are just too valuable to the industry to be overlooked. Whether you’re looking to be acquired or seeking to make a last stand by merging with your former competitors, knowing what your unique selling points are and leading with them will stand you in good stead.
In conclusion, the market data industry is at the precipice of a major change, driven by the emergence of hyperscalers in both the worlds of data center development (hardware) and market data provision (software). This will lead to a period of great disruption, but also to a host of new opportunities. As technical challenges regarding latency are resolved, the industry will likely see new distribution infrastructures and common APIs emerging for the seamless transmission of market data. This transformation poses risks for incumbents and the onus will be on them to embrace change, foster collaboration and focus on differentiating themselves in the coming years. Finally, I believe the availability of AI tools at scale will lead to waves of innovation that will result in new predictive models and products to revolutionize, and (one hopes) democratize how we access market data and perform analysis. See you on the other side!
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