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Head-to-head · Stream Processing Software

Apache Flink vs Apache Spark

  • 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
Apache Spark #8 in Stream Processing Software 8.6/10 Free plan Free plan✓ 0 of 3 features Visit Apache Spark

Apache Flink leads on 0 checks, Apache Spark on 0, and 4 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 planboth
  • Most featuresApache Flink · 3 of 3

Apache Flink scores higher on our rubric for stream processing software: 9.2 against 8.6 out of 10; our editors rank them #2 and #8.

Apache Flink is the better fit for teams needing a full-featured open stream engine. Apache Spark is the better fit for mature teams combining batch and streaming.

  • Apache Flink fits best

    Teams needing a full-featured open stream engine

  • Apache Spark fits best

    Mature teams combining batch and streaming

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Side by side

Feature Apache Flink 9.2/10 Visit ↗ Apache Spark 8.6/10 Visit ↗
At a glance
Editor score 9.2 8.6
Ranking #2 in Stream Processing Software #8 in Stream Processing Software
Best for Teams needing a full-featured open stream engine Mature teams combining batch and streaming
Pricing model Free Free
Starting price Free plan Free plan
Free plan ✓ ✓
Free trial — —
Deployment Self-hosted Self-hosted
Support Docs Community, Docs
Integrations 15 integrations 20 integrations
Built for Small business, Mid-market, Enterprise Small business, Mid-market, Enterprise
Features Apache Flink 3/3 · Apache Spark 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
  • Structured Streaming supports incremental stream processing
  • Broad APIs across Python, SQL, Scala, Java, and R
  • Connects to major data sources, clusters, and lakehouse systems
Cons
  • Self-hosted operation requires team-managed deployment and infrastructure
  • Deployment options center on standalone, Kubernetes, and YARN
  • DataStream programs are Java-based
  • Self-hosted deployment requires cluster infrastructure
  • Streaming is one part of a broader batch-focused platform
  • Not a hosted ETL SaaS product with subscription tiers
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 →

Apache Spark is an open-source distributed computing engine for large-scale data processing and analytics. It is aimed at developers, data engineers, analysts, and organizations processing data across clusters. Structured Streaming…

Read the review →
  1. Apache FlinkStream Processing Software 9.2Free plan
  2. Apache SparkStream Processing Software 8.6Free plan

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

  • Apache Spark — where it wins

    • Structured Streaming supports incremental stream processing
    • Broad APIs across Python, SQL, Scala, Java, and R
    • Connects to major data sources, clusters, and lakehouse systems

    Where it doesn't

    • Self-hosted deployment requires cluster infrastructure
    • Streaming is one part of a broader batch-focused platform
    • Not a hosted ETL SaaS product with subscription tiers

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