Redis Streams vs Apache Kafka | Unicorn Factories

Overview

Redis Streams and Apache Kafka are both log-based streaming platforms, but they target different use cases and operational profiles. Redis Streams excels at lightweight, low-latency scenarios while Kafka dominates high-throughput, long-retention workloads.

Feature Comparison

Capability	Redis Streams	Apache Kafka
Throughput	100K-1M msg/sec per node	1M+ msg/sec per node
Persistence	In-memory with optional disk	Disk-based with OS page cache
Retention	Memory-limited (GBs)	Disk-limited (TBs/PBs)
Latency	Sub-millisecond	2-10ms typical
Consumer Groups	Yes	Yes
Exactly-Once	Via Lua scripting	Native support
Partitioning	Cluster mode	Native partitions
Operational Complexity	Low	High

When to Choose Redis Streams

Edge deployments: Limited memory and CPU at the edge
Low latency requirements: Sub-millisecond read/write needed
Simple operations: Small team, no dedicated Kafka expertise
Short retention: Hours to days of event history
Existing Redis infrastructure: Already running Redis for caching/sessions

When to Choose Apache Kafka

High throughput: Millions of messages per second
Long retention: Months or years of event history
Complex stream processing: Kafka Streams, ksqlDB for transformations
Enterprise scale: Multiple data centers, compliance requirements
Exactly-once semantics: Critical for financial/audit use cases

Can They Coexist?

Yes. Common pattern: Redis Streams at the edge for buffering and local processing, with Kafka Connect pushing to Kafka for centralized analytics and long-term storage.