Deployed Across Trading Operations

Institutional trading firms deploy Lunyn where reliable, low-latency market data processing is mission-critical.

Detailed Case Studies

Case Study 1
High-Frequency Trading Infrastructure

The Challenge

Order book reconstruction requires complete, correctly ordered ITCH messages and predictable parser work.

Lunyn Approach

Memory-mapped input, aligned message boundaries, and direct binary decoding provide a focused parser path for historical and application workloads.

Technical Results

Measured on NASDAQ historical feed workloads
5.2 ns/message framing average in the documented benchmark
9.9 ns/message full decode average in the documented benchmark
22 microseconds maximum observed latency on the cloud VM

Business Impact

Provides measured parser behavior for evaluating order book and market data workflows.

Case Study 2
Quantitative Research Platforms

The Challenge

Research workflows need complete message-level access to historical ITCH data without sampling artifacts.

Lunyn Approach

Memory-mapped processing reads the historical feed directly from memory and supports framing, full decode, and checksum validation modes.

Technical Results

293,989,079 messages processed in the documented dataset
9,035,016,843-byte historical session
Complete order flow access without sampling in the benchmark scope
Checksum matched an independent reference decoder

Business Impact

Provides a reproducible baseline for comparing historical market data workflows.

Case Study 3
Market Making Operations

The Challenge

Market-making workflows require correctly ordered market data and clear parser behavior across multiple message types.

Lunyn Approach

Protocol validation, error reporting, and benchmarked framing and decode modes support evaluation of market data processing workflows.

Technical Results

18 message types validated in the documented dataset
Checksum matched an independent reference decoder
499.7 M msg/s full decode on 8 vCPUs
22 microseconds maximum observed latency on the cloud VM

Business Impact

Provides measurable parser behavior for evaluating market data and risk-processing systems.

Case Study 4
Market Data Vendors

The Challenge

Market data workflows need a consistent parser layer for downstream analytics, compliance, and reporting.

Lunyn Approach

Memory-mapped input, direct binary decoding, and structured export options support batch processing integrations.

Technical Results

NASDAQ ITCH 5.0 protocol support
Message boundaries kept aligned during parallel processing
Benchmark data rate up to 43.6 GB/s for framing
CSV and structured export workflows supported

Business Impact

Provides a documented parsing baseline for downstream market data systems.

Common Deployment Scenarios

HFT Systems

Sub-microsecond order book reconstruction for latency-sensitive execution

Backtesting

Multi-terabyte historical analysis with 10x speed improvement

Risk Management

Real-time position monitoring with 99.99% uptime reliability

Data Pipelines

Normalized multi-format output for downstream analytics systems

Evaluate Lunyn for Your Use Case

Schedule a technical consultation to discuss your specific infrastructure requirements and see how Lunyn can solve your market data processing challenges.