Using caches (Redis), brokers (Kafka, RabbitMQ)

Using caches and message brokers in betting platforms

Betting systems operate under high load and require instant data processing: live bets, streaming events, calculations and the interface must be synchronized in real time. That is why caching systems (Redis) and message brokers (Kafka, RabbitMQ) play a key role in the architecture. They provide speed, stability and scalability critical to gameplay.

Why do you need a cache in betting

Redis is used as high-performance in-memory storage for:

• Caching matches, coefficients, event statuses
• TTL data storage (bet timers, live updates)
• Quick access to user sessions, shopping carts, stories
• Rate-limiting, betting limits, anti-fraud
• Buffering between slow bases and interface

Redis is used in pub/sub mode for instant alerts between microservices.

What message brokers do

Kafka and RabbitMQ manage data flows between microservices and external providers:

Use Case	Kafka	RabbitMQ
Sports Event Flow	High Bandwidth	Limited Volumes
Update coefficients	Great fit	Suitable for queues
Notifications, alerts	Redundant	Ideal in simple scenarios
Analytics and logging	Streaming at ClickHouse	Better Kafka or log collectors

Kafka vs RabbitMQ - the choice depends on the task

Criterion	Kafka	RabbitMQ
Throughput	Very High (mln msg/sec)	Medium
Order	Guaranteed	Maintained
Message Storage	Long Term (Disk)	Short Term (Memory/Disk)
Load management	Highly scalable	Easy to install and configure
Ideal for	Threads, logs, real-time API	Backend, notifications, queues

Examples of architectural solutions

Redis + PostgreSQL: fast delivery of matches with backup to the database
Kafka + Go services: event reception and coefficient streaming
RabbitMQ + Node. js: processing bonuses, fluffs, e-mail events
Kafka → ClickHouse: streaming analytics, live betting tracking

What it gives the platform

Event response - within milliseconds
Unloading DB and API using caches and queues
Scalability of microservices without rigid binding
Reliability improvement: failures do not affect the entire system
Ability to build real-time analytics and alerting

Caches and brokers are the real-time core of betting systems. Redis provides lightning-fast data access, Kafka and RabbitMQ manage event flows, and together they enable scalable, fault-tolerant and stable platform behavior in live load. Without them, not a single serious betting product can be built today.