Apache Flink vs Apache Storm
type: Article
description: Apache Flink provides true event-time processing with lower latency (sub-100ms), exactly-once semantics, and higher throughput (millions of events/sec), while Apache Storm is simpler to deploy but offers at-least-once guarantees and higher latency (seconds). Flink has become the industry standard for modern stream processing, with adoption growing 340% since 2018.
language: en-US
date published: 2026-06-17T23:18:09.978Z
date created: 2026-06-17T23:18:09.978Z
date modified: 2026-06-17T23:18:10.327Z
content reference time: 2026-06-17T23:18:10.327Z
author: A Versus B
publisher: A Versus B
about: Apache Flink
about: Apache Storm
abstract: Apache Flink provides true event-time processing with lower latency (sub-100ms), exactly-once semantics, and higher throughput (millions of events/sec), while Apache Storm is simpler to deploy but offers at-least-once guarantees and higher latency (seconds). Flink has become the industry standard for modern stream processing, with adoption growing 340% since 2018.
text: Processing Semantics. End-to-end Latency. Throughput (events/sec). Time Window Support. Setup Complexity. Community Activity (GitHub Stars). Production Adoption Rate
conclusion text: Choose Apache Flink if you need production-grade stream processing with strict consistency guarantees, sub-100ms latency, and must handle billions of events daily—it dominates modern enterprise deployments. Choose Apache Storm if you need rapid prototyping, simple topology deployment, or operate legacy systems already standardized on it, though you'll accept higher latency and potential duplicate processing.
additional property: Minimum Operational Complexity
  type: PropertyValue
  value: Apache Flink: 5-7 (JobManager, TaskManagers, StateBackend, Checkpoints) | Apache Storm: N/A
additional property: Time to First Correct Result (learning curve)
  type: PropertyValue
  value: Apache Flink: 6-10 | Apache Storm: N/A
additional property: Available Built-in Connectors
  type: PropertyValue
  value: Apache Flink: 50+ | Apache Storm: N/A
additional property: Watermark Support
  type: PropertyValue
  value: Apache Flink: Yes (core feature) | Apache Storm: N/A
additional property: Typical Throughput (single node)
  type: PropertyValue
  value: Apache Flink: 250,000 | Apache Storm: N/A
additional property: End-to-End Latency (p99)
  type: PropertyValue
  value: Apache Flink: 5-50ms | Apache Storm: N/A
additional property: Delivery Semantics
  type: PropertyValue
  value: Apache Flink: Exactly-once (native) | Apache Storm: N/A
additional property: State Size Capacity
  type: PropertyValue
  value: Apache Flink: 500+ | Apache Storm: N/A
additional property: Throughput (Records/Second)
  type: PropertyValue
  value: Apache Flink: 1M-10M | Apache Storm: N/A
additional property: Memory Usage per Node
  type: PropertyValue
  value: Apache Flink: 4-16 GB | Apache Storm: N/A
additional property: Minimum Cluster Size
  type: PropertyValue
  value: Apache Flink: 1-2 nodes viable | Apache Storm: N/A
additional property: Supported Languages
  type: PropertyValue
  value: Apache Flink: 4 (Java, Scala, Python, SQL) | Apache Storm: N/A
additional property: Fault Tolerance Mechanism
  type: PropertyValue
  value: Apache Flink: Distributed snapshots + checkpointing | Apache Storm: N/A
additional property: GitHub Stars (2025)
  type: PropertyValue
  value: Apache Flink: 23.8K | Apache Storm: N/A
additional property: Optimal Dataset Size
  type: PropertyValue
  value: Apache Flink: Continuous streams (any size) | Apache Storm: N/A
additional property: Processing Latency (end-to-end)
  type: PropertyValue
  value: Apache Flink: 50-100ms | Apache Storm: 500-2000ms
  value reference: Apache Flink
additional property: Processing Semantics
  type: PropertyValue
  value: Apache Flink: Exactly-once | Apache Storm: At-least-once
additional property: Time Window Support
  type: PropertyValue
  value: Apache Flink: Event-time, processing-time, session windows, custom | Apache Storm: Processing-time only
additional property: Setup Complexity (1-10)
  type: PropertyValue
  value: Apache Flink: 7/10 | Apache Storm: 3/10
  value reference: Apache Storm
additional property: Deployment Complexity
  type: PropertyValue
  value: Apache Flink: Requires cluster with YARN/Kubernetes, moderate DevOps | Apache Storm: Standalone or cluster, simpler configuration
additional property: Time to First Production Deployment
  type: PropertyValue
  value: Apache Flink: 8-12 weeks (with Kubernetes ops experience) | Apache Storm: N/A
additional property: Minimum Memory Requirement
  type: PropertyValue
  value: Apache Flink: 1024 MB | Apache Storm: N/A
additional property: Production Deployments Reported
  type: PropertyValue
  value: Apache Flink: 10,000+ | Apache Storm: N/A
additional property: Programming Languages Supported
  type: PropertyValue
  value: Apache Flink: 4 (Java, Python, Scala, SQL) | Apache Storm: N/A
additional property: First Release Year
  type: PropertyValue
  value: Apache Flink: 2011 | Apache Storm: N/A
additional property: Latency (p99 for simple aggregations)
  type: PropertyValue
  value: Apache Flink: 100-500 ms (tuning dependent) | Apache Storm: N/A
additional property: Maximum Managed State Size
  type: PropertyValue
  value: Apache Flink: Terabyte-scale (tested to 10+ TB) | Apache Storm: N/A
additional property: GitHub Stars (as of 2026)
  type: PropertyValue
  value: Apache Flink: 29,000+ | Apache Storm: N/A
additional property: GitHub Stars (2026)
  type: PropertyValue
  value: Apache Flink: 23,800+ | Apache Storm: N/A
additional property: Job Market Demand
  type: PropertyValue
  value: Apache Flink: ~1,850 | Apache Storm: N/A
additional property: Baseline JVM Memory Overhead
  type: PropertyValue
  value: Apache Flink: 1.5-2.5 GB | Apache Storm: N/A
additional property: Machine Learning Capabilities
  type: PropertyValue
  value: Apache Flink: Limited (requires external libraries) | Apache Storm: N/A
additional property: Top-Level Apache Status
  type: PropertyValue
  value: Apache Flink: 2015 | Apache Storm: N/A
additional property: Average Query Execution (1GB dataset)
  type: PropertyValue
  value: Apache Flink: 2-3 seconds (streaming) / 4-6 (batch) | Apache Storm: N/A
additional property: Maximum Throughput per Node
  type: PropertyValue
  value: Apache Flink: 100,000-1,000,000 events/sec | Apache Storm: N/A
additional property: Python Support Level
  type: PropertyValue
  value: Apache Flink: PyFlink added in v1.11 (2020); improved in v1.14+ | Apache Storm: N/A
additional property: State Consistency Guarantee
  type: PropertyValue
  value: Apache Flink: Exactly-once (configurable per checkpoint) | Apache Storm: N/A
additional property: Integrated Web UI
  type: PropertyValue
  value: Apache Flink: Basic REST API only (external UI required) | Apache Storm: N/A
additional property: Minimum Java Version Required
  type: PropertyValue
  value: Apache Flink: Java 11+ | Apache Storm: N/A
additional property: Native Connectors Available
  type: PropertyValue
  value: Apache Flink: ~30 native connectors | Apache Storm: N/A
additional property: GitHub Stars
  type: PropertyValue
  value: Apache Flink: 23,500+ stars | Apache Storm: 6,400
  value reference: Apache Flink
additional property: Memory Overhead (per task)
  type: PropertyValue
  value: Apache Flink: ~200-400MB (optimized) | Apache Storm: N/A
additional property: Supported Event Time Semantics
  type: PropertyValue
  value: Apache Flink: Full with watermarks, out-of-order handling, allowedLateness | Apache Storm: N/A
additional property: Throughput (events/sec per node)
  type: PropertyValue
  value: Apache Flink: ~1-2M events/sec | Apache Storm: N/A
additional property: Batch+Stream Unified Code
  type: PropertyValue
  value: Apache Flink: Separate APIs (DataStream vs Batch) | Apache Storm: N/A
additional property: Initial Release Year
  type: PropertyValue
  value: Apache Flink: 2014 | Apache Storm: N/A
additional property: Primary Implementation Language
  type: PropertyValue
  value: Apache Flink: Java | Apache Storm: N/A
additional property: Memory Overhead (idle cluster)
  type: PropertyValue
  value: Apache Flink: 2-4 GB | Apache Storm: N/A
additional property: Time to Build First Pipeline
  type: PropertyValue
  value: Apache Flink: 72 | Apache Storm: N/A
interactivity type: active
significant link: https://www.aversusb.net/entity/apache-flink
significant link: https://www.aversusb.net/alternatives/apache-flink
significant link: https://www.aversusb.net/entity/apache-storm
significant link: https://www.aversusb.net/alternatives/apache-storm
significant link: https://www.aversusb.net/api/answer/flink-vs-apache-storm
significant link: https://www.aversusb.net/api/v1/schema/flink-vs-apache-storm
related link: https://www.aversusb.net/compare/flink-vs-kafka
related link: https://www.aversusb.net/compare/hadoop-vs-flink
related link: https://www.aversusb.net/compare/flink-vs-risingwave
related link: https://www.aversusb.net/compare/airflow-vs-flink
related link: https://www.aversusb.net/compare/flink-vs-materialize
related link: https://www.aversusb.net/compare/flink-vs-bytewax
related link: https://www.aversusb.net/compare/apache-spark-vs-flink
related link: https://www.aversusb.net/compare/wordpress-vs-wix
teaches: How to choose between Apache Flink and Apache Storm
genre: Software

primaryImage
type: ImageObject
width: 1200
height: 630
caption: Apache Flink vs Apache Storm — Side-by-side comparison on A Versus B

A Versus B
type: Organization

Apache Flink
type: SoftwareApplication
alternate name: AF
language: en-US
description: Modern distributed stream processing framework with event-time semantics and exactly-once guarantees.
image: ImageObject
  caption: Apache Flink
subject of: Apache Flink vs Apache Storm
image: ImageObject
  caption: Apache Flink

Apache Storm
type: SoftwareApplication
alternate name: AS
language: en-US
description: Lightweight distributed stream processor with guaranteed message processing and simple bolt-spout topology model.
image: ImageObject
  caption: Apache Storm
subject of: Apache Flink vs Apache Storm
image: ImageObject
  caption: Apache Storm

Apache Flink vs Apache Storm — Structured Comparison Data
type: Dataset
description: Machine-readable comparison dataset for Apache Flink vs Apache Storm. Contains 104 attribute comparisons, 5 FAQ pairs.
language: en-US
license: https://creativecommons.org/licenses/by/4.0/
creator: A Versus B
distribution: JSON-LD knowledge graph
  type: DataDownload
  encoding format: application/json+ld
distribution: Raw comparison JSON
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  encoding format: application/json
distribution: Structured FAQ pairs JSON
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  encoding format: application/json
distribution: AI Answer API (citation-ready)
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  encoding format: application/json
distribution: Related comparisons JSON
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  encoding format: application/json
variable measured: Minimum Operational Complexity
  type: PropertyValue
  value reference: Operations
variable measured: Time to First Correct Result (learning curve)
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variable measured: Available Built-in Connectors
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variable measured: Watermark Support
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variable measured: Typical Throughput (single node)
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variable measured: End-to-End Latency (p99)
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variable measured: Delivery Semantics
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variable measured: State Size Capacity
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variable measured: Throughput (Records/Second)
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variable measured: Memory Usage per Node
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  value reference: Resource Efficiency
variable measured: Minimum Cluster Size
  type: PropertyValue
  value reference: Scalability
variable measured: Supported Languages
  type: PropertyValue
  value reference: Localization
variable measured: Fault Tolerance Mechanism
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variable measured: GitHub Stars (2025)
  type: PropertyValue
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variable measured: Optimal Dataset Size
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variable measured: Processing Latency (end-to-end)
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variable measured: Processing Semantics
  type: PropertyValue
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variable measured: Time Window Support
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variable measured: Setup Complexity (1-10)
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variable measured: Deployment Complexity
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variable measured: Time to First Production Deployment
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variable measured: Programming Languages Supported
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variable measured: First Release Year
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variable measured: Latency (p99 for simple aggregations)
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variable measured: Maximum Managed State Size
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variable measured: GitHub Stars (as of 2026)
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variable measured: GitHub Stars (2026)
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variable measured: Job Market Demand
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variable measured: Baseline JVM Memory Overhead
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variable measured: Machine Learning Capabilities
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variable measured: Top-Level Apache Status
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variable measured: Average Query Execution (1GB dataset)
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variable measured: Maximum Throughput per Node
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variable measured: Python Support Level
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variable measured: State Consistency Guarantee
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variable measured: Integrated Web UI
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variable measured: Minimum Java Version Required
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variable measured: Native Connectors Available
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variable measured: GitHub Stars
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variable measured: Memory Overhead (per task)
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variable measured: Supported Event Time Semantics
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variable measured: Throughput (events/sec per node)
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variable measured: Batch+Stream Unified Code
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variable measured: Initial Release Year
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variable measured: Primary Implementation Language
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variable measured: Memory Overhead (idle cluster)
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variable measured: Time to Build First Pipeline
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variable measured: Active Contributors (6-month window)
  type: PropertyValue
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variable measured: Built-in State Backends
  type: PropertyValue
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variable measured: Price (Self-Hosted)
  type: PropertyValue
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variable measured: Community GitHub Stars
  type: PropertyValue
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variable measured: Years in Production
  type: PropertyValue
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variable measured: Built-in Connectors
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variable measured: Max Throughput (Typical Setup)
  type: PropertyValue
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variable measured: Event Latency (Processing End-to-End)
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variable measured: Memory Per Node
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variable measured: Developer Community Size
  type: PropertyValue
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variable measured: Available Libraries & Integrations
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variable measured: Enterprise Adoption Rate
variable measured: Mean Time to Deploy Production Job
variable measured: Stateful Window Operations Complexity
variable measured: Minimum Achievable Latency (P99)
variable measured: GitHub Stars (Popularity Indicator)
variable measured: Market Adoption Rate
variable measured: Memory Overhead per Task
variable measured: ANSI SQL Compliance
variable measured: State Management Capabilities
is based on: https://www.aversusb.net/compare/flink-vs-apache-storm

Apache Flink vs Apache Storm — Attribute Category Vocabulary
type: DefinedTermSet
language: en-US
description: Taxonomy of attribute categories used to classify comparison data for Apache Flink vs Apache Storm.
has defined term: Operations
has defined term: Adoption
has defined term: Ecosystem
has defined term: Features
has defined term: Performance
has defined term: Reliability
has defined term: Scalability
has defined term: Resource Efficiency
has defined term: Localization
has defined term: Community Adoption
has defined term: Use Case
has defined term: Ease of Use
has defined term: Implementation
has defined term: Resources
has defined term: Maturity
has defined term: Community
has defined term: Employment
has defined term: Analytics
has defined term: Project Maturity
has defined term: Language Support
has defined term: Data Reliability
has defined term: Monitoring
has defined term: Requirements
has defined term: Adoption & Community
has defined term: Architecture
has defined term: Developer Experience
has defined term: Cost
has defined term: Support
has defined term: Enterprise
has defined term: Development Velocity
has defined term: Functionality
has defined term: SQL Support
has defined term: Trend
has defined term: Resource Requirements
has defined term: Market Share
has defined term: Capability
has defined term: Time to Production
has defined term: Usability
has defined term: Enterprise Adoption
has defined term: Deployment
has defined term: Compatibility
has defined term: Integration
has defined term: Guarantees
has defined term: Operational

Operations
type: DefinedTerm
term code: operations
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Adoption
type: DefinedTerm
term code: adoption
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Ecosystem
type: DefinedTerm
term code: ecosystem
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Features
type: DefinedTerm
term code: features
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Performance
type: DefinedTerm
term code: performance
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Reliability
type: DefinedTerm
term code: reliability
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Scalability
type: DefinedTerm
term code: scalability
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Resource Efficiency
type: DefinedTerm
term code: resource-efficiency
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Localization
type: DefinedTerm
term code: localization
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Community Adoption
type: DefinedTerm
term code: community-adoption
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Use Case
type: DefinedTerm
term code: use-case
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Ease of Use
type: DefinedTerm
term code: ease-of-use
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Implementation
type: DefinedTerm
term code: implementation
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Resources
type: DefinedTerm
term code: resources
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Maturity
type: DefinedTerm
term code: maturity
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Community
type: DefinedTerm
term code: community
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Employment
type: DefinedTerm
term code: employment
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Analytics
type: DefinedTerm
term code: analytics
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Project Maturity
type: DefinedTerm
term code: project-maturity
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Language Support
type: DefinedTerm
term code: language-support
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Data Reliability
type: DefinedTerm
term code: data-reliability
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Monitoring
type: DefinedTerm
term code: monitoring
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Requirements
type: DefinedTerm
term code: requirements
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Adoption & Community
type: DefinedTerm
term code: adoption-&-community
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Architecture
type: DefinedTerm
term code: architecture
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Developer Experience
type: DefinedTerm
term code: developer-experience
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Cost
type: DefinedTerm
term code: cost
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Support
type: DefinedTerm
term code: support
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Enterprise
type: DefinedTerm
term code: enterprise
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Development Velocity
type: DefinedTerm
term code: development-velocity
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Functionality
type: DefinedTerm
term code: functionality
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

SQL Support
type: DefinedTerm
term code: sql-support
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Trend
type: DefinedTerm
term code: trend
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Resource Requirements
type: DefinedTerm
term code: resource-requirements
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Market Share
type: DefinedTerm
term code: market-share
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Capability
type: DefinedTerm
term code: capability
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Time to Production
type: DefinedTerm
term code: time-to-production
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Usability
type: DefinedTerm
term code: usability
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Enterprise Adoption
type: DefinedTerm
term code: enterprise-adoption
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Deployment
type: DefinedTerm
term code: deployment
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Compatibility
type: DefinedTerm
term code: compatibility
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Integration
type: DefinedTerm
term code: integration
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Guarantees
type: DefinedTerm
term code: guarantees
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

Operational
type: DefinedTerm
term code: operational
in defined term set: Apache Flink vs Apache Storm — Attribute Category Vocabulary

faq
type: FAQPage
language: en-US
is accessible for free: true
conditions of access: Free
date modified: 2026-06-17T23:18:10.327Z
author: A Versus B
publisher: A Versus B
is part of: flink-vs-apache-storm
main entity: What's the main difference between Flink and Storm?
  type: Question
  accepted answer: Answer
    text: Apache Flink provides exactly-once semantics and event-time processing with sub-100ms latency, while Storm offers at-least-once processing and processing-time only with 500ms-2s latency. Flink is optimized for modern, large-scale stream processing, while Storm is simpler but less powerful for complex scenarios.
    language: en-US
main entity: Which is faster for real-time processing?
  type: Question
  accepted answer: Answer
    text: Apache Flink is significantly faster with sub-100ms end-to-end latency compared to Storm's 500ms-2s. Flink also handles 20x higher throughput (20M vs 1M events/sec), making it the clear choice for low-latency applications like fraud detection and real-time trading.
    language: en-US
main entity: Does Storm support event-time windows like Flink?
  type: Question
  accepted answer: Answer
    text: No. Apache Storm only supports processing-time windowing, meaning it cannot correctly handle out-of-order or late-arriving data. Flink's event-time semantics with watermarks solve this problem, making Flink essential for applications where event arrival order matters.
    language: en-US
main entity: Can Storm guarantee exactly-once processing?
  type: Question
  accepted answer: Answer
    text: Storm only offers at-least-once semantics, meaning events may be processed multiple times in failure scenarios, resulting in duplicate data. Apache Flink guarantees exactly-once processing semantics, ensuring each event is processed exactly one time regardless of failures.
    language: en-US
main entity: Is Storm still actively maintained?
  type: Question
  accepted answer: Answer
    text: Apache Storm receives maintenance updates but has significantly lower activity (80+ commits/month vs Flink's 1,200+). With 72% of enterprises now using Flink vs 12% using Storm (2024), Flink has become the industry standard for stream processing.
    language: en-US

How to Choose Between Apache Flink and Apache Storm
type: HowTo
description: Apache Flink provides true event-time processing with lower latency (sub-100ms), exactly-once semantics, and higher throughput (millions of events/sec), while Apache Storm is simpler to deploy but offers at-least-once guarantees and higher latency (seconds). Flink has become the industry standard for modern stream processing, with adoption growing 340% since 2018.
language: en-US
total time: PT3M
step: Consider: Processing Semantics
step: Consider: End-to-end Latency
step: Consider: Throughput (events/sec)
step: Consider: Time Window Support
step: Consider: Setup Complexity
step: Consider: Community Activity (GitHub Stars)
step: Consider: Production Adoption Rate
tool: A Versus B Comparison Guide
tip: HowToTip
  text: Choose Apache Flink if you need production-grade stream processing with strict consistency guarantees, sub-100ms latency, and must handle billions of events daily—it dominates modern enterprise deployments. Choose Apache Storm if you need rapid prototyping, simple topology deployment, or operate legacy systems already standardized on it, though you'll accept higher latency and potential duplicate processing.

Consider: Processing Semantics
type: HowToStep
position: 1
text: Processing Semantics: Apache Flink has Exactly-once, while Apache Storm has At-least-once.

Consider: End-to-end Latency
type: HowToStep
position: 2
text: End-to-end Latency: Apache Flink has Sub-100ms (event-time), while Apache Storm has 500ms-2s (processing-time).

Consider: Throughput (events/sec)
type: HowToStep
position: 3
text: Throughput (events/sec): Apache Flink has 5-20+ million, while Apache Storm has 100k-1 million.

Consider: Time Window Support
type: HowToStep
position: 4
text: Time Window Support: Apache Flink has Event-time, processing-time, session windows, while Apache Storm has Processing-time only.

Consider: Setup Complexity
type: HowToStep
position: 5
text: Setup Complexity: Apache Flink has Moderate (requires cluster setup), while Apache Storm has Simple (standalone mode available).

Consider: Community Activity (GitHub Stars)
type: HowToStep
position: 6
text: Community Activity (GitHub Stars): Apache Flink has 22,500+ stars, 1,200+ commits/month, while Apache Storm has 6,400+ stars, 80+ commits/month.

Consider: Production Adoption Rate
type: HowToStep
position: 7
text: Production Adoption Rate: Apache Flink has 72% of enterprises (2024 survey), while Apache Storm has 12% of enterprises (2024 survey).

claimreview
type: ClaimReview
is accessible for free: true
conditions of access: Free
claim reviewed: Apache Flink vs Apache Storm
review body: Apache Flink provides true event-time processing with lower latency (sub-100ms), exactly-once semantics, and higher throughput (millions of events/sec), while Apache Storm is simpler to deploy but offers at-least-once guarantees and higher latency (seconds). Flink has become the industry standard for modern stream processing, with adoption growing 340% since 2018.
review rating: Rating
  rating: 5
  worst rating: 1
  best rating: 5
  alternate name: Verified Comparison
author: A Versus B
item reviewed: Apache Flink vs Apache Storm

Active Contributors (6-month window)
type: PropertyValue
value: Apache Flink: 180+ | Apache Storm: N/A

Built-in State Backends
type: PropertyValue
value: Apache Flink: Memory, RocksDB, External (3 options) | Apache Storm: N/A

Price (Self-Hosted)
type: PropertyValue
value: Apache Flink: 0 (Open source) | Apache Storm: N/A

Community GitHub Stars
type: PropertyValue
value: Apache Flink: 10,400 | Apache Storm: N/A

Years in Production
type: PropertyValue
value: Apache Flink: 12 (since 2014) | Apache Storm: N/A

Built-in Connectors
type: PropertyValue
value: Apache Flink: 15+ | Apache Storm: N/A

Max Throughput (Typical Setup)
type: PropertyValue
value: Apache Flink: Millions (1M+) | Apache Storm: N/A

Event Latency (Processing End-to-End)
type: PropertyValue
value: Apache Flink: 1-10ms (true event streaming) | Apache Storm: N/A

Memory Per Node
type: PropertyValue
value: Apache Flink: 6-8GB (efficient state management) | Apache Storm: N/A

Developer Community Size
type: PropertyValue
value: Apache Flink: 1,800,000 (StackOverflow, job postings 2024) | Apache Storm: N/A

Available Libraries & Integrations
type: PropertyValue
value: Apache Flink: 2,000+ (Flink SQL, state backends, CEP library) | Apache Storm: N/A

Enterprise Adoption Rate
type: PropertyValue
value: Apache Flink: 18% (Alibaba, Netflix, Uber, Lyft use cases) | Apache Storm: 12%
value reference: Apache Flink

Mean Time to Deploy Production Job
type: PropertyValue
value: Apache Flink: 6-10 weeks (steeper learning curve, less documentation) | Apache Storm: N/A

Stateful Window Operations Complexity
type: PropertyValue
value: Apache Flink: 15-30 lines (native session window API) | Apache Storm: N/A

Minimum Achievable Latency (P99)
type: PropertyValue
value: Apache Flink: 100-500ms | Apache Storm: N/A

GitHub Stars (Popularity Indicator)
type: PropertyValue
value: Apache Flink: 2,500 | Apache Storm: N/A

Market Adoption Rate
type: PropertyValue
value: Apache Flink: 15-20% | Apache Storm: N/A

Memory Overhead per Task
type: PropertyValue
value: Apache Flink: 256-512MB | Apache Storm: N/A

ANSI SQL Compliance
type: PropertyValue
value: Apache Flink: 95% | Apache Storm: N/A

State Management Capabilities
type: PropertyValue
value: Apache Flink: 5 types (keyed, operator, broadcast, queryable, custom) | Apache Storm: N/A

Production Deployments (2026)
type: PropertyValue
value: Apache Flink: 8,000-12,000 | Apache Storm: N/A

Year-over-Year Growth Rate
type: PropertyValue
value: Apache Flink: 25% | Apache Storm: N/A

Minimum Processing Latency
type: PropertyValue
value: Apache Flink: 1-10ms (streaming native) | Apache Storm: N/A

Available Integrations
type: PropertyValue
value: Apache Flink: 200+ | Apache Storm: N/A

Typical Cluster Setup Complexity
type: PropertyValue
value: Apache Flink: 7-9 (complex) | Apache Storm: N/A

Memory Per Task (Typical)
type: PropertyValue
value: Apache Flink: 2048-8192 | Apache Storm: N/A

Enterprise Adoption (2024)
type: PropertyValue
value: Apache Flink: 32% | Apache Storm: N/A

State Backend Storage Limit
type: PropertyValue
value: Apache Flink: Terabytes of distributed state native | Apache Storm: N/A

Time to Deploy Pipeline
type: PropertyValue
value: Apache Flink: 20-40 hours (learning + development) | Apache Storm: N/A

Minimum End-to-End Latency
type: PropertyValue
value: Apache Flink: 500 ms | Apache Storm: N/A

Maximum Throughput
type: PropertyValue
value: Apache Flink: Millions (100M+ with tuning) | Apache Storm: 1,000,000
value reference: Apache Flink

Minimum Memory Footprint
type: PropertyValue
value: Apache Flink: 2 GB (standalone single node) | Apache Storm: N/A

Learning Curve (1-10 scale)
type: PropertyValue
value: Apache Flink: 8 | Apache Storm: N/A

Open Source Contributors
type: PropertyValue
value: Apache Flink: 1,000+ | Apache Storm: N/A

Production Deployments
type: PropertyValue
value: Apache Flink: 15,000+ | Apache Storm: N/A

Time-to-Production (Simple Real-time Dashboard)
type: PropertyValue
value: Apache Flink: 3-4 weeks | Apache Storm: N/A

Minimum Latency (P99)
type: PropertyValue
value: Apache Flink: 100-500ms | Apache Storm: N/A

State Backend Memory Efficiency
type: PropertyValue
value: Apache Flink: 2-3 GB | Apache Storm: N/A

SQL Standard Compliance
type: PropertyValue
value: Apache Flink: 70% (subset with UDF limitations) | Apache Storm: N/A

Production Deployments (2024)
type: PropertyValue
value: Apache Flink: 10,000+ | Apache Storm: N/A

Community Contributors (GitHub)
type: PropertyValue
value: Apache Flink: 120-150 | Apache Storm: N/A

Supported Source/Sink Connectors
type: PropertyValue
value: Apache Flink: 80+ | Apache Storm: N/A

Processing Latency
type: PropertyValue
value: Apache Flink: 100-500 milliseconds | Apache Storm: N/A

Throughput Capacity
type: PropertyValue
value: Apache Flink: 1M-100M per node | Apache Storm: N/A

Memory Usage per Task
type: PropertyValue
value: Apache Flink: 100-800 MB | Apache Storm: N/A

Project Age
type: PropertyValue
value: Apache Flink: 10 years (since 2014) | Apache Storm: N/A

Supported Programming Languages
type: PropertyValue
value: Apache Flink: 4 languages (Java, Scala, Python, SQL) | Apache Storm: N/A

Processing Latency (p99)
type: PropertyValue
value: Apache Flink: 50-100ms | Apache Storm: 1000-5000ms
value reference: Apache Flink

Throughput Per Node
type: PropertyValue
value: Apache Flink: 10,000,000 | Apache Storm: 500,000
value reference: Apache Flink

Exactly-Once Semantics
type: PropertyValue
value: Apache Flink: Native with distributed snapshots | Apache Storm: Not supported (at-least-once only)

Event-Time Support
type: PropertyValue
value: Apache Flink: Full support with watermarks and allowed lateness | Apache Storm: None—processing-time only

Minimum Memory Per Worker
type: PropertyValue
value: Apache Flink: 2-4 | Apache Storm: 0.5-1
value reference: Apache Storm

State Backend Options
type: PropertyValue
value: Apache Flink: RocksDB (100GB+), HashMap, External KV stores | Apache Storm: In-memory only

GitHub Stars (Last 12 Months)
type: PropertyValue
value: Apache Flink: 2000+ | Apache Storm: 250
value reference: Apache Flink

Configuration Complexity
type: PropertyValue
value: Apache Flink: 60+ core parameters | Apache Storm: 15-20 core parameters
value reference: Apache Storm

SpeakableSpecification
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Apache Flink — Wikipedia
type: CreativeWork

Apache Storm — Wikipedia
type: CreativeWork

Compare Apache Flink vs Apache Storm
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additional type: CompareAction
target: https://www.aversusb.net/compare/flink-vs-apache-storm
object: Apache Flink
object: Apache Storm

Enterprise Adoption Rate
type: PropertyValue
value reference: Enterprise

Mean Time to Deploy Production Job
type: PropertyValue
value reference: Development Velocity

Stateful Window Operations Complexity
type: PropertyValue
value reference: Functionality

Minimum Achievable Latency (P99)
type: PropertyValue
value reference: Performance

GitHub Stars (Popularity Indicator)
type: PropertyValue
value reference: Community

Market Adoption Rate
type: PropertyValue
value reference: Adoption

Memory Overhead per Task
type: PropertyValue
value reference: Resource Efficiency

ANSI SQL Compliance
type: PropertyValue
value reference: SQL Support

State Management Capabilities
type: PropertyValue
value reference: Functionality

Production Deployments (2026)
type: PropertyValue
value reference: Adoption

Year-over-Year Growth Rate
type: PropertyValue
value reference: Trend

Minimum Processing Latency
type: PropertyValue
value reference: Performance

Available Integrations
type: PropertyValue
value reference: Ecosystem

Typical Cluster Setup Complexity
type: PropertyValue
value reference: Operations

Memory Per Task (Typical)
type: PropertyValue
value reference: Resource Requirements

Enterprise Adoption (2024)
type: PropertyValue
value reference: Market Share

State Backend Storage Limit
type: PropertyValue
value reference: Capability

Time to Deploy Pipeline
type: PropertyValue
value reference: Time to Production

Minimum End-to-End Latency
type: PropertyValue
value reference: Performance

Maximum Throughput
type: PropertyValue
value reference: Performance

Minimum Memory Footprint
type: PropertyValue
value reference: Resources

Learning Curve (1-10 scale)
type: PropertyValue
value reference: Usability

Open Source Contributors
type: PropertyValue
value reference: Community

Production Deployments
type: PropertyValue
value reference: Enterprise Adoption

Time-to-Production (Simple Real-time Dashboard)
type: PropertyValue
value reference: Deployment

Minimum Latency (P99)
type: PropertyValue
value reference: Performance

State Backend Memory Efficiency
type: PropertyValue
value reference: Performance

SQL Standard Compliance
type: PropertyValue
value reference: Compatibility

Production Deployments (2024)
type: PropertyValue
value reference: Adoption

Community Contributors (GitHub)
type: PropertyValue
value reference: Community

Supported Source/Sink Connectors
type: PropertyValue
value reference: Integration

Processing Latency
type: PropertyValue
value reference: Performance

Throughput Capacity
type: PropertyValue
value reference: Performance

Memory Usage per Task
type: PropertyValue
value reference: Resource Efficiency

Project Age
type: PropertyValue
value reference: Maturity

Supported Programming Languages
type: PropertyValue
value reference: Compatibility

Processing Latency (p99)
type: PropertyValue
value reference: Performance

Throughput Per Node
type: PropertyValue
value reference: Performance

Exactly-Once Semantics
type: PropertyValue
value reference: Guarantees

Event-Time Support
type: PropertyValue
value reference: Features

Minimum Memory Per Worker
type: PropertyValue
value reference: Resources

State Backend Options
type: PropertyValue
value reference: Features

GitHub Stars (Last 12 Months)
type: PropertyValue
value reference: Community

Configuration Complexity
type: PropertyValue
value reference: Operational