Apache Kafka vs Apache Spark
A side-by-side comparison of two Data Stream Processing AI agents — to help you pick the right one.
Apache Kafka
Apache Kafka is a distributed event streaming platform designed to handle high-throughput, real-time data feeds. It enables applications to publish, subscribe to, store, and process streams of records in a fault-tolerant manner.
Apache Spark
Apache Spark is a unified analytics engine for large-scale data processing, supporting batch processing, real-time stream processing, and machine learning. It provides in-memory computing capabilities to speed up iterative algorithms and interactive queries.
| Apache Kafka | Apache Spark | |
|---|---|---|
| Category | Data Stream Processing | Data Stream Processing |
| Open source | Yes | Yes |
| Self-hostable | Yes | Yes |
| Skill level | Intermediate | Intermediate |
| Pricing | Open Source | Open Source |
Apache Kafka: what it solves
It solves the challenge of reliably processing and managing large-scale, real-time data streams across distributed systems.
Apache Spark: what it solves
Enables efficient processing of large-scale data workloads by distributing computations across clusters, reducing latency and improving throughput compared to traditional batch systems.