Market Data Infrastructure: What Capital Market Firms Need to Build, Scale, and Optimize

 Explore the topics shaping modern market data infrastructure, from foundational concepts and provider models to architecture, cost, and performance. 

Key Concepts

» What is Market Data Infrastructure?

• Market data infrastructure is the foundation firms use to access, process, and deliver market data across trading and operational systems. It supports everything from real-time pricing and execution to risk management, compliance, and analytics. 

» What Type of Financial Data Providers are There? 

•  Financial data providers supply the market data, analytics, and delivery models firms need to support trading, risk, compliance, and research. These providers can include exchanges, consolidated feed providers, managed data vendors, and specialized firms focused on particular markets, workflows, or infrastructure needs. 

» What is a Consolidated Tape? 

•  A consolidated tape aggregates quotes and trades from multiple trading venues into a single market-wide view. By bringing fragmented data together in one feed, it helps support price discovery, transparency, and a more consistent view of market activity. 

» How Market Data Fees Can Inform Your Infrastructure Plans

•  Market data fees affect more than budget. They also shape how firms think about distribution, entitlement, user access, and where different types of data belong across the stack. Used strategically, they can help guide smarter infrastructure and sourcing decisions. 

» What is the True Cost of Building Market Data Infrastructure In-house?

• Building market data infrastructure in-house often means more than upfront development. It can also involve longer deployment timelines, ongoing maintenance, and the operational burden of keeping pace with exchange-driven change. Exegy’s Part I summary frames those costs in terms of both resources and long-term scalability. 

» Level 2 Market Data: What Level Supports Your Trading Strategy? 

• Not every workflow needs the same depth of market data. Understanding the differences between top-of-book, price book, and order book data can help firms align market data consumption with strategy, workflow requirements, and budget. Exegy’s Level 2 blog is specifically about matching the level of data to trading needs and market data costs. 

»  Why is Yesterday’s Infrastructure Today’s Financial Loss? 

• OPRA resiliency isn’t just “add backups”—it’s designing for A/B stream redundancy, clean failover, and recovery behavior that keeps downstream systems consistent during peak bursts. This section covers what redundancy really changes (bandwidth and processing can effectively double when you take both streams) and why firms rehearse failover and capacity readiness during scheduled industry test windows.

»  How Can the Right Market Data Vendor Help Firms Maximize Efficiency? 

• The right market data vendor can do more than deliver data. It can help firms improve adaptability, stay ahead of exchange-driven change, maintain reliability under pressure, control infrastructure costs, and build for future growth. Exegy’s blog closes on five qualities firms should look for when evaluating a market data vendor. 

Our findings, based on real-world data from a Tier 1 global bank and Exegy’s more than 20 years of market data expertise, reveal that building in-house software-based market data infrastructure is significantly more expensive, time-consuming, and operationally burdensome than vendor solutions.

Key Findings

» In-House Software Development Is Expensive

• The first in-house software feed handler costs $1.8 million, while full North American equities and commodities coverage (20 markets) exceeds $4.7 million.
• In-house builds are ~8x more expensive than Exegy’s for full North American equities coverage.

» Software Maintenance Is a Recurring Cost Drain

• Annual in-house maintenance costs exceed $3.5 million, while Exegy’s fully managed solution reduces these recurring expenses by ~2.6x.
• In 2023 alone, Exegy managed 8,356 exchange notifications and 481 exchange-directed changes (EDCs), with 35% requiring code updates that demand extensive development and QA efforts.
• Managing EDCs in-house adds hidden operational risks due to regulatory and exchange-driven protocol updates.

» Vendor Solutions Offer Time Savings & Resource Optimization

• Exegy delivers production-ready solutions in 4-6 months, compared to 3.5 years for in-house teams—a 7x speed advantage.
• In-house development diverts skilled engineers and resources from strategic projects, increasing overhead and opportunity costs.
• Partnering with Exegy reduces internal workloads, allowing firms to focus on core business innovations.

Strategic Takeaways

Building market data feed handlers in-house may seem like a way to retain control, but the true cost in time, resources, and ongoing maintenance is substantial. 

Vendor solutions provide:

• Cost Savings: Lower total cost of ownership (TCO) by reducing development and maintenance expenses
• Faster Time to Market: Immediate access to fully managed market data solutions
• Reduced Operational Overhead: Vendors absorbing the burden of ongoing exchange-driven updates and system monitoring

For firms evaluating field-programmable gate array (FPGA)-based alternatives, our companion white paper details the costs and complexities of hardware-accelerated market data processing.

Market data infrastructure underpins every aspect of modern capital markets, from trading and risk management to compliance and analytics. As data volumes grow and latency requirements tighten, firms are increasingly challenged to design systems that are not only fast and reliable, but also scalable and cost-efficient. These FAQs address the core concepts behind market data infrastructure—what it is, how it works, and why it matters—helping firms better understand the architectural, operational, and strategic considerations that shape today’s real-time market data environments.

Q: What is Market Data Infrastructure? 

Market data infrastructure refers to the systems, technologies, and networks that collect, process, normalize, and distribute financial market information. It underpins trading, risk, compliance, and analytics by ensuring firms can access accurate, real-time data across global markets. 

Q: Why is Market Data Infrastructure Important in Capital Markets? 

It is essential because every trading decision depends on timely and reliable data. Even small delays or inconsistencies in price or order book information can impact execution quality, pricing accuracy, and risk exposure. Modern markets rely on this infrastructure to enable liquidity, price discovery, and automation at scale. 

Q: What are the Main Components of Market Data Infrastructure? 

 Key components typically include exchange data feeds, feed handlers, normalization layers, distribution systems, and downstream consumption engines such as trading platforms, risk systems, and analytics tools. Feed handlers are especially critical, as they convert raw exchange data into usable, standardized formats. 

Q: What is a Market Data Feed Handler? 

 A feed handler is a software component that ingests raw exchange data and processes it into a structured format for internal systems. It manages tasks such as decoding exchange protocols, sequencing messages, handling gaps, and distributing normalized data with minimal latency. 

Q:  Why is Latency so Important in Market Data Infrastructure? 

Latency determines how quickly market information reaches trading and risk systems. In modern electronic markets, even microsecond-level delays can affect competitiveness, especially for latency-sensitive strategies. This has led to ongoing investment in low-latency networks and optimized processing architectures. 

Q:  What Causes Complexity in Market Data Infrastructure? 

Complexity comes from fragmented exchange ecosystems, multiple data formats, regulatory requirements, and the sheer volume of data generated across global markets. Firms often must manage multiple feeds, normalize inconsistent data, and maintain infrastructure that adapts to constant exchange-driven changes. 

Q:  What is the Difference Between Raw and Consolidated Market Data Feeds?  

 Raw feeds come directly from exchanges and provide the most granular, low-latency data. Consolidated feeds aggregate data from multiple venues and normalize it into a single view, which simplifies consumption but can introduce latency trade-offs depending on the use case. 

Q:  How Do Firms Typically Consume Market Data?  

Most firms consume data through a layered architecture: exchange feeds are processed by feed handlers, normalized into internal formats, and then distributed to trading systems, risk engines, analytics platforms, and downstream applications across the organization.

Q:  What are the Biggest Challenges in Managing Market Data Infrastructure? 

 The primary challenges include rising data volumes, increasing infrastructure costs, ongoing maintenance demands, exchange-driven updates, and the need to balance performance, scalability, and operational efficiency. 

Q:  How is Market Data Infrastructure Evolving? 

It is shifting toward more centralized, scalable, and software-defined architectures, with greater use of specialized hardware acceleration, managed services, and cloud-enabled distribution models to reduce complexity and improve efficiency.