Market Data Feed Handlers
Market data feed handlers are specialized software components that receive, process, and normalize raw market data from exchanges and other data providers into standardized formats for consumption by trading systems. They play a critical role in managing the high-volume, low-latency flow of market information in modern financial markets.
Core functions of market data feed handlers
Market data feed handlers serve as the crucial first point of contact between external market data sources and internal trading systems. Their primary responsibilities include:
- Protocol handling and decoding
- Data normalization and standardization
- Message sequencing and gap detection
- Rate limiting and throttling
- Distribution to downstream consumers
Next generation time-series database
QuestDB is an open-source time-series database optimized for market and heavy industry data. Built from scratch in Java and C++, it offers high-throughput ingestion and fast SQL queries with time-series extensions.
Performance considerations
Feed handlers must process massive volumes of market data with minimal latency. Key performance factors include:
- Message throughput capacity
- Processing latency
- Memory efficiency
- CPU utilization
- Network I/O optimization
The performance of feed handlers directly impacts the ability of trading systems to react to market changes and maintain accurate pricing models.
Next generation time-series database
QuestDB is an open-source time-series database optimized for market and heavy industry data. Built from scratch in Java and C++, it offers high-throughput ingestion and fast SQL queries with time-series extensions.
Market data types and processing
Feed handlers typically process several types of market data:
- Level 1 (best bid/offer)
- Level 2 (order book depth)
- Trade reports
- Reference data
- Corporate actions
- Statistical data
Each data type requires specific processing rules and normalization steps to ensure consistent handling across different venues and data sources.
Integration with trading infrastructure
Feed handlers integrate with various components of the trading infrastructure:
The normalized data from feed handlers enables:
- Real-time price discovery
- Order book maintenance
- Trade matching validation
- Market making decisions
- Risk calculations
Resilience and fault tolerance
Feed handlers must implement robust error handling and recovery mechanisms:
- Automatic failover
- Gap recovery
- Sequence number tracking
- Message replay capabilities
- Connection management
- Error logging and alerting
These mechanisms ensure continuous market data flow even during adverse conditions.
Regulatory considerations
Feed handlers play a crucial role in regulatory compliance:
- Timestamp accuracy requirements
- Audit trail maintenance
- Data quality monitoring
- Market abuse detection
- Best execution validation
They must maintain accurate records of all received and processed market data for regulatory reporting and analysis.
Modern trends and developments
Current trends in feed handler technology include:
- Hardware acceleration
- FPGA implementation
- Cloud deployment models
- Machine learning integration
- Real-time analytics capabilities
These developments continue to push the boundaries of performance and functionality in market data processing.