July 01, 2025

Understanding Real-Time Market Data: Types, Sources, and What Matters Most to Traders

In modern trading, real-time market data is the foundation of every decision and execution. But not all real-time data is created equal. The format, source, and delivery method of market data can directly impact your trading performance, latency profile, and overall cost.

For traders — from high-frequency quants to discretionary swing traders — understanding the different types of real-time data and how they align with your strategy and infrastructure is essential to trading success.

Types of Real-Time Market Data: Raw, Normalized, and Packaged

Raw Market Data

Raw data streams deliver unfiltered, tick-by-tick updates directly from the exchange’s matching engines. This data includes every trade, quote update, and order book change as it happens—without aggregation or transformation.

Common use case:

High-frequency trading (HFT), latency-sensitive arbitrage, and algorithmic strategies requiring the fastest possible data.

Characteristics:

Extremely high bandwidth and volume
Requires sophisticated systems to decode and process
Often delivered via multicast feeds or direct exchange connections with co-location

Cost:

Typically the most expensive due to infrastructure needs and licensing fees.

Normalized Market Data

Normalized data takes raw feeds and standardizes them across multiple exchanges and asset types, cleaning and organizing the data into a consistent format. This makes it easier for trading systems to integrate and reduces complexity.

Common use case:

Quantitative traders, discretionary traders using automated signals, and firms prioritizing reliability and ease of integration over absolute lowest latency.

Characteristics:

Slightly higher latency than raw feeds due to processing time
Simplified and consistent data structure
Supports multi-venue and multi-asset trading

Cost:

More affordable and easier to integrate than raw data, balances performance with operational efficiency.

Packaged Market Data

Packaged data refers to market data that has been pre-processed, aggregated, and often enriched with analytics or visualizations for display purposes. This is the type of data seen in trading terminals, charting software, and broker platforms.

Common use case:

Retail and institutional traders relying on visualization and alerts rather than ultra-low-latency execution.

Characteristics:

Designed for human consumption with charting, alerts, and historical context
Latency is acceptable for discretionary trading but not for high-frequency strategies

Cost:

Often included with trading platforms or available at lower cost.

Display Data vs. Non-Display Data: Usage and Licensing

Market data is also categorized based on how it’s used, which impacts licensing and cost:

Display Data is data shown on screens, like market depth windows, charts, and dashboards. This requires display licensing and is used by traders manually watching the market.
Non-Display Data is data consumed programmatically by algorithms or automated systems without being rendered on a screen. This often carries different licensing terms and may be more expensive, reflecting its use in high-speed trading engines.

Understanding whether your strategy requires display or non-display data licenses can significantly affect your budget and compliance.

Market Data Sources and Delivery Methods

The source and delivery of market data determine latency and reliability:

Exchange Direct Feeds: Data received straight from exchanges via dedicated infrastructure, usually colocated within or near exchange data centers to minimize latency. Ideal for traders needing the fastest possible updates.
Aggregated Feeds: Consolidated data from multiple exchanges provided by third-party vendors, normalized and packaged for broader use. These feeds prioritize convenience and coverage over absolute speed.
Cloud-Based Feeds: Market data streamed via the cloud, providing flexibility but generally with higher latency than colocated direct feeds.

Each option varies in cost, speed, and integration complexity. Your choice depends on your trading strategy and technology stack.

Aligning Market Data with Your Trading Profile

Choosing the right market data boils down to:

Latency Needs:

If you’re a scalper or HFT firm, raw direct feeds with co-location are critical.
Swing traders or discretionary traders may prefer normalized or packaged data that’s easier to work with.

Cost Considerations:

Raw data and non-display licenses can be costly.
Normalized and packaged feeds often offer a better balance of cost and performance.

Trading Style and Infrastructure:

Algorithmic strategies require programmatic access to data with API integrations.
Manual traders benefit from visualization and alerting features.

How Lime Trading Supports Your Real-Time Market Data Needs

At Lime Trading, we offer institutional-grade real-time data solutions tailored to your trading style and latency profile:

Lime Trader Web: Free, real-time data with rich visualization tools for screen traders monitoring markets live.
Lime REST API: Access normalized market data for NMS equities, options, and OTC stocks, suitable for algorithmic strategies requiring reliable and structured data.
Lime Direct & Lime Binary (Citrius Multicast): Ultra-low-latency, raw or near-raw data feeds with co-location options, designed for traders who demand the fastest market updates and deepest order book access.

Conclusion

Real-time market data is not a one-size-fits-all commodity. Your choice between raw, normalized, or packaged data—and whether you use display or non-display licenses—should reflect your strategy, latency needs, and budget.

Investing in the right type of real-time data infrastructure can dramatically improve execution quality, reduce slippage, and unlock trading opportunities.

Discover how Lime Trading’s suite of real-time data feeds and APIs can give you the competitive edge you need in today’s fast-paced markets.

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