Use cases_
Sports Betting
Enable instant odds calculations, live in-play betting, and rapid risk management. Offer more dynamic and engaging betting options while maintaining financial stability.
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Business requirements
The sports betting industry requires stream processing capabilities that can handle massive volumes of real-time data from multiple sports events simultaneously. The system must provide instantaneous odds calculations, real-time risk analysis, fraud detection, and seamless integration with various betting platforms and payment systems.
Technical challenges
Implementing real-time data processing in sports betting presents several technical challenges. These include processing high-velocity data streams from multiple live events, ensuring ultra-low latency for time-sensitive operations like in-play betting, maintaining data consistency across distributed systems, and scaling to handle peak loads during major sporting events. The solution must also be highly available, secure against potential cyber threats, and compliant with varying regulatory requirements across different jurisdictions.
Why RisingWave?
Efficient data handlingRisingWave ingests and processes large volumes of high-velocity data from various sources such as messaging platforms and databases in real-time.
Broad connectivityIt offers robust connectors for popular data systems, enabling easy data input and output.
Wide compatibilityAs a Postgres-compatible database, RisingWave works with many analytics tools through standard Postgres drivers.
Low latencyRisingWave delivers results in milliseconds, using real-time materialized views that update continuously.
Complex transformationsIt efficiently performs operations like filtering, joins, and aggregates across multiple data sources.
Easy metric creationNew metrics can be set up with just one or two SQL queries.
Data consistencyRisingWave ensures all queries access the same version of data, guaranteeing correct and consistent results.
Simple scalingYou can add new nodes as needed without system downtime.
Use cases
Live odds calculationContinuously updating betting odds based on real-time event data and betting patterns.
In-play bettingOffering and managing bets on ongoing events with rapidly changing conditions.
Risk managementReal-time analysis of betting patterns to identify and mitigate potential financial risks.
Fraud detectionMonitoring betting activities to identify suspicious patterns and prevent fraudulent bets.
Personalized offeringsAnalyzing user behavior in real-time to provide tailored betting suggestions and promotions.
Automated market makingAdjusting betting lines and limits automatically based on real-time data and algorithms.
Cash-out optionsProviding dynamic cash-out values for bets based on current event status and odds.
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