The AWS Moment in Market Data

When Amazon launched AWS, most enterprises were still buying servers. Infrastructure meant hardware procurement, long deployment cycles, and heavy operational overhead. 

AWS didn't just move servers to the cloud. It changed how organizations thought about infrastructure entirely. The question shifted from "How many servers do we own?" to "How flexibly can we scale?" Market data is now approaching the same inflection point. 

From Ownership to Orchestration 

For decades, financial institutions treated market data as something to acquire and operate internally — securing feeds, negotiating vendor contracts, managing entitlements. It was fundamentally a procurement function. 

That framing is becoming obsolete. 

Data volumes are expanding rapidly, driven by AI and machine learning adoption. Cloud delivery is now standard across exchanges, trading systems, and data providers. The question is no longer how to own market data, but how to orchestrate it effectively. 

Cloud computing didn't eliminate infrastructure complexity — it shifted where control lived. The future of market data follows the same logic. It's not about eliminating feeds or vendors. It's about redefining the control layer: vendor-neutral integration, centralized visibility into usage and cost, standardized normalization across sources, and embedded governance. 

Infrastructure as Strategy 

Historically, data spend was treated as a cost center — necessary overhead, managed defensively. But market data infrastructure now directly impacts trading latency, risk analytics accuracy, AI model performance, and regulatory resilience. 

Vendor neutrality matters here for the same reason it matters in cloud. Institutions cannot control price increases, API changes, or vendor consolidation. But they can control how dependent they are on any single provider — and that flexibility increasingly functions as a risk management imperative, not just an architectural preference. 

AI Is the Catalyst 

AI systems require clean, normalized datasets; consistent schemas across vendors; and reliable, scalable delivery. Raw feeds alone are insufficient. Without structured orchestration underneath, data complexity compounds rather than generating value. AI doesn't simplify infrastructure — it amplifies the need for it. 

The Shift 

Market data strategy is moving through three phases: acquisition, operation, and orchestration. Most firms have mastered the first two. The third is now decisive. 

AWS didn't win because companies wanted fewer servers. It won because companies needed more agility. Market data is entering that same moment. 

The competitive question is no longer "How much data do we have?" It's "How effectively do we control, standardize, and scale it?"