G2 Vendor Directory

Apache Kafka vs. Google Cloud Dataflow

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

MetricApache Kafka

by The Apache Software Foundation

Google Cloud Dataflow

by Google

Overall rating4.54.2
Review count13244
Ease of use8.88.3
Ease of setup8.38.2
Quality of support8.28.6
Meets requirements9.09.1
NPS72.44094542.857143
Small Business22.7%36.4%
Mid-Market31.1%31.8%
Enterprise46.2%31.8%
Total page views388219
Total LLM citations1,699272

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

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