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Head-to-head · Stream Processing Software

Apache Flink vs Google Cloud Dataflow

  • Updated Oct 2026
  • Both researched from official sources
  • 4 checks side by side
Higher score Apache Flink #2 in Stream Processing Software 9.2/10 Free plan Free plan✓ 3 of 3 features Visit Apache Flink
Google Cloud Dataflow #4 in Stream Processing Software 9.0/10 Paid ✓ 0 of 3 features Visit Google Cloud

Apache Flink leads on 1 check, Google Cloud Dataflow on 0, and 3 are even. Who comes out ahead on the 4 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.

Our verdict

  • Highest scoreApache Flink · 9.2/10
  • Free planonly Apache Flink
  • Most featuresApache Flink · 3 of 3

Apache Flink scores higher on our rubric for stream processing software: 9.2 against 9.0 out of 10; our editors rank them #2 and #4.

Apache Flink offers free plan; Google Cloud Dataflow doesn't.

Apache Flink is the better fit for teams needing a full-featured open stream engine. Google Cloud Dataflow is the better fit for google Cloud teams running managed pipelines.

  • Apache Flink fits best

    Teams needing a full-featured open stream engine

  • Google Cloud Dataflow fits best

    Google Cloud teams running managed pipelines

Advertiser disclosure: iTechGuides is reader-supported. Vendors can pay for top positions in our rankings and for a place on other products' pages, and we may earn a commission when you click some links. Bought places stand at the number bought; this page and our disclosure say so. Paying vendors may get a fuller, more detailed review from our editors, and that review can change their score. How we rank.

Side by side

Feature Apache Flink 9.2/10 Visit ↗ Google Cloud Dataflow 9.0/10 Visit ↗
At a glance
Editor score 9.2 9.0
Ranking #2 in Stream Processing Software #4 in Stream Processing Software
Best for Teams needing a full-featured open stream engine Google Cloud teams running managed pipelines
Pricing model Free Paid
Starting price Free plan Not checked yet
Free plan ✓ (best) —
Free trial — —
Deployment Self-hosted Cloud
Support Docs Docs, Community, Live chat, Phone, Tickets
Integrations 15 integrations 14 integrations
Built for Small business, Mid-market, Enterprise Mid-market, Enterprise
Features Apache Flink 3/3 · Google Cloud Dataflow 0/3
SQL processing ✓ (best) Not checked yet
Stateful processing ✓ (best) Not checked yet
Event-time windows ✓ (best) Not checked yet
Specs
Deployment model Self-hosted Not checked yet
Supported languages Java, Python, Scala Not checked yet
Source connectors 7 Not checked yet
Our review
Pros
  • Stateful processing with event-time windows and late-data handling
  • Exactly-once consistency with checkpoint-based recovery
  • SQL, DataStream API, and broad connector support
  • Runs both batch and streaming pipelines with autoscaling
  • Supports managed Beam connectors, CDC templates, SQL, and Python
  • Connects with Google Cloud, databases, Kafka, and analytics tools
Cons
  • Self-hosted operation requires team-managed deployment and infrastructure
  • Deployment options center on standalone, Kubernetes, and YARN
  • DataStream programs are Java-based
  • Usage-based pricing does not provide fixed subscription tiers
  • No free plan is listed
  • Cloud deployment may not suit teams seeking self-hosted processing
Our verdict

Apache Flink is an open-source distributed processing engine for bounded and unbounded data streams. It is designed for engineering and data-platform teams building event-driven applications, streaming analytics, data pipelines, and ETL…

Read the review →

Google Cloud Dataflow is a managed service for running Apache Beam pipelines across batch and streaming workloads. It is aimed at engineering and data teams building scalable processing and integration workflows, with support for Java,…

Read the review →
  1. Apache FlinkStream Processing Software 9.2Free plan
  2. Google Cloud DataflowStream Processing Software 9.0Paid

Strengths and trade-offs

  • Apache Flink — where it wins

    • Stateful processing with event-time windows and late-data handling
    • Exactly-once consistency with checkpoint-based recovery
    • SQL, DataStream API, and broad connector support

    Where it doesn't

    • Self-hosted operation requires team-managed deployment and infrastructure
    • Deployment options center on standalone, Kubernetes, and YARN
    • DataStream programs are Java-based

  • Google Cloud Dataflow — where it wins

    • Runs both batch and streaming pipelines with autoscaling
    • Supports managed Beam connectors, CDC templates, SQL, and Python
    • Connects with Google Cloud, databases, Kafka, and analytics tools

    Where it doesn't

    • Usage-based pricing does not provide fixed subscription tiers
    • No free plan is listed
    • Cloud deployment may not suit teams seeking self-hosted processing

More comparisons

All stream processing software comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Last updated · How we research and update