G2 Vendor Directory

Spark Streaming vs. Apache Kafka

A side-by-side comparison based on G2 review data.

MetricSpark Streaming

by The Apache Software Foundation

Apache Kafka

by The Apache Software Foundation

Overall rating4.24.5
Review count40132
Ease of use8.48.8
Ease of setup7.98.3
Quality of support8.88.2
Meets requirements9.19.0
NPS39.47368472.440945
Small Business30.8%22.7%
Mid-Market43.6%31.1%
Enterprise25.6%46.2%
Total page views74388
Total LLM citations661,699

Spark Streaming

Spark Streaming brings Apache Spark's language-integrated API to stream processing, letting you write streaming jobs the same way you write batch jobs. It supports Java, Scala and Python. Spark Streaming recovers both lost work and operator state (e.g. sliding windows) out of the box, without any extra code on your part.

Pros

    Apache Kafka

    Apache Kafka is an open-source distributed event streaming platform developed by the Apache Software Foundation. It is designed to handle real-time data feeds with high throughput and low latency, making it ideal for building data pipelines, streaming analytics, and integrating data across various systems. Kafka enables organizations to publish, store, and process streams of records in a fault-tolerant and scalable manner, supporting mission-critical applications across diverse industries.

    Pros

    • Scalability
    • Real-time Data
    • Performance Efficiency
    • Performance
    • Reliability
    • Easy Integrations