G2 Vendor Directory

Google Cloud Dataflow vs. Apache Kafka

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

MetricGoogle Cloud Dataflow

by Google

Apache Kafka

by The Apache Software Foundation

Overall rating4.24.5
Review count44132
Ease of use8.38.8
Ease of setup8.28.3
Quality of support8.68.2
Meets requirements9.19.0
NPS42.85714372.440945
Small Business36.4%22.7%
Mid-Market31.8%31.1%
Enterprise31.8%46.2%
Total page views219388
Total LLM citations2721,699

Google Cloud Dataflow

Cloud Dataflow is a fully-managed service for transforming and enriching data in stream (real time) and batch (historical) modes with equal reliability and expressiveness -- no more complex workarounds or compromises needed. And with its serverless approach to resource provisioning and management, you have access to virtually limitless capacity to solve your biggest data processing challenges, while paying only for what you use.

Pros

  • Features
  • Real-time Analytics
  • Insights
  • Real-Time Processing
  • Easy Management
  • Speed

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