Hadoop vs Apache Flink
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description: Hadoop is a batch processing framework optimized for large-scale data storage and processing with high latency, while Apache Flink is a stream processing engine designed for real-time data processing with sub-second latency. Flink processes continuous data streams natively, whereas Hadoop processes static data in batches.
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Hadoop vs Apache Flink
type: Article
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abstract: Hadoop is a batch processing framework optimized for large-scale data storage and processing with high latency, while Apache Flink is a stream processing engine designed for real-time data processing with sub-second latency. Flink processes continuous data streams natively, whereas Hadoop processes static data in batches.
description: Hadoop is a batch processing framework optimized for large-scale data storage and processing with high latency, while Apache Flink is a stream processing engine designed for real-time data processing with sub-second latency. Flink processes continuous data streams natively, whereas Hadoop processes static data in batches.
language: en-US
main entity of page: Hadoop vs Apache Flink
content reference time: 2026-07-09T17:30:42.631Z
author: A Versus B
publisher: A Versus B
date published: 2026-07-09T17:30:42.592Z
date created: 2026-07-09T17:30:42.592Z
date modified: 2026-07-09T17:30:42.631Z
text: Choose Hadoop if you need robust batch processing for large historical datasets, have existing investments in the ecosystem, and can tolerate latency of minutes to hours. Choose Flink if you require real-time or near-real-time stream processing, need complex stateful computations, or want unified batch and streaming capabilities with lower resource overhead.
genre: Software
potential action: ReadAction
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potential action: Compare Apache Hadoop vs Apache Flink
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  object: Apache Hadoop
  object: Apache Flink
about: Apache Hadoop
about: Apache Flink
mentions: Processing Model
mentions: Latency
mentions: State Management
mentions: Memory Efficiency
mentions: Ecosystem Maturity
mentions: Community Size
mentions: Use Case Fit
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citation: Apache Hadoop — Wikipedia
citation: Apache Flink — Wikipedia
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A Versus B
type: Organization

Apache Hadoop
type: SoftwareApplication
description: Distributed batch processing framework for large-scale data storage and analysis using MapReduce paradigm.
alternate name: AH
language: en-US
subject of: Hadoop vs Apache Flink

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

Hadoop vs Apache Flink — Comparison Data
type: Dataset
description: Structured comparison data for Hadoop vs Apache Flink with 164 attributes.
language: en-US
license: https://creativecommons.org/licenses/by/4.0/
creator: A Versus B
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distribution: AI Answer API (citation-ready)
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variable measured: Total Cost of Ownership (5 years, 100TB)
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variable measured: Supported Languages
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variable measured: Throughput Capacity

Hadoop vs Apache Flink — Attribute Category Vocabulary
type: DefinedTermSet
language: en-US
description: Taxonomy of attribute categories used to classify comparison data for Hadoop vs Apache Flink.
has defined term: Cost
has defined term: Developer Experience
has defined term: Operations
has defined term: Performance
has defined term: Capacity
has defined term: Scalability
has defined term: Reliability
has defined term: Resource Efficiency
has defined term: Localization
has defined term: Community Adoption
has defined term: Use Case
has defined term: Deployment
has defined term: Pricing
has defined term: Features
has defined term: Capability
has defined term: Compliance
has defined term: Infrastructure
has defined term: History
has defined term: Compatibility
has defined term: Industry
has defined term: User Experience
has defined term: Flexibility
has defined term: Architecture
has defined term: Implementation
has defined term: Governance
has defined term: Collaboration
has defined term: Customization
has defined term: Economics
has defined term: Community
has defined term: Maturity
has defined term: Adoption & Community
has defined term: Adoption
has defined term: Ecosystem
has defined term: Ease of Use
has defined term: Resources
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: 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: Time to Production
has defined term: Usability
has defined term: Enterprise Adoption
has defined term: Integration
has defined term: Guarantees
has defined term: Operational

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

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

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

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

Capacity
type: DefinedTerm
term code: capacity
in defined term set: Hadoop vs Apache Flink — Attribute Category Vocabulary

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

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

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

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

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

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

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

Pricing
type: DefinedTerm
term code: pricing
in defined term set: Hadoop vs Apache Flink — Attribute Category Vocabulary

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

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

Compliance
type: DefinedTerm
term code: compliance
in defined term set: Hadoop vs Apache Flink — Attribute Category Vocabulary

Infrastructure
type: DefinedTerm
term code: infrastructure
in defined term set: Hadoop vs Apache Flink — Attribute Category Vocabulary

History
type: DefinedTerm
term code: history
in defined term set: Hadoop vs Apache Flink — Attribute Category Vocabulary

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

Industry
type: DefinedTerm
term code: industry
in defined term set: Hadoop vs Apache Flink — Attribute Category Vocabulary

User Experience
type: DefinedTerm
term code: user-experience
in defined term set: Hadoop vs Apache Flink — Attribute Category Vocabulary

Flexibility
type: DefinedTerm
term code: flexibility
in defined term set: Hadoop vs Apache Flink — Attribute Category Vocabulary

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

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

Governance
type: DefinedTerm
term code: governance
in defined term set: Hadoop vs Apache Flink — Attribute Category Vocabulary

Collaboration
type: DefinedTerm
term code: collaboration
in defined term set: Hadoop vs Apache Flink — Attribute Category Vocabulary

Customization
type: DefinedTerm
term code: customization
in defined term set: Hadoop vs Apache Flink — Attribute Category Vocabulary

Economics
type: DefinedTerm
term code: economics
in defined term set: Hadoop vs Apache Flink — Attribute Category Vocabulary

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

faq
type: FAQPage
language: en-US
is accessible for free: true
conditions of access: Free
date modified: 2026-07-09T17:30:42.631Z
author: A Versus B
publisher: A Versus B
is part of: Hadoop vs Apache Flink
main entity: Can Hadoop process streaming data in real-time?
  type: Question
  accepted answer: Answer
    text: Hadoop is fundamentally a batch processing framework and cannot natively process streaming data in real-time. While Hadoop can be combined with streaming tools like Kafka or Storm, the processing itself still occurs in batches (typically every few minutes). For true real-time streaming, Flink or Spark Streaming are better choices.
    language: en-US
main entity: Can Flink replace Hadoop for large-scale batch processing?
  type: Question
  accepted answer: Answer
    text: Yes, Flink can handle large-scale batch processing and often does so more efficiently than Hadoop due to in-memory processing and lower latency. However, Hadoop remains superior for extremely large historical datasets (100+ TB) where cost per TB is critical, as HDFS provides unmatched data locality and fault tolerance at petabyte scale.
    language: en-US
main entity: Which is easier to learn and deploy?
  type: Question
  accepted answer: Answer
    text: Flink has a steeper initial learning curve due to event time semantics and state management complexity. However, Flink's unified API is easier to maintain long-term compared to Hadoop's MapReduce paradigm. For deployment, Hadoop has more mature operational tooling and broader DevOps familiarity across the industry.
    language: en-US
main entity: What are the cost differences between Hadoop and Flink?
  type: Question
  accepted answer: Answer
    text: Hadoop typically costs 30-50% less per TB for storage due to commodity hardware efficiency and 3x replication, making it ideal for cold data storage. Flink requires more memory but fewer nodes, resulting in 20-40% lower operational costs for streaming workloads. The choice depends on whether you prioritize storage cost (Hadoop) or compute efficiency (Flink).
    language: en-US
main entity: Can both frameworks work together?
  type: Question
  accepted answer: Answer
    text: Yes, many organizations use Hadoop for batch ETL and historical analytics while using Flink for real-time streams from the same data sources. Flink can read from HDFS, and both can integrate with Kafka, making a hybrid architecture viable for complex data pipelines requiring both batch and real-time processing.
    language: en-US

Data Locality Advantage
type: PropertyValue
value reference: Performance

Custom Algorithm Support (1-5 scale)
type: PropertyValue
value reference: Customization

Query Performance (10TB TPC-DS benchmark)
type: PropertyValue
value reference: Performance

Annual Cost (100TB, 24/7 usage)
type: PropertyValue
value reference: Economics

Compute & Storage Coupling
type: PropertyValue
value reference: Architecture

SQL Query Support
type: PropertyValue
value reference: Capability

Data Recovery (Time Travel)
type: PropertyValue
value reference: Features

Required DevOps Team Size
type: PropertyValue
value reference: Operations

Community Size (GitHub Stars)
type: PropertyValue
value reference: Community

Throughput Capacity
type: PropertyValue
value reference: Performance

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

Project Age
type: PropertyValue
value reference: Maturity

GitHub Stars
type: PropertyValue
value reference: Adoption & Community

State Backend Options
type: PropertyValue
value reference: Features

Minimum Cluster Size
type: PropertyValue
value reference: Scalability

Minimum Operational Complexity
type: PropertyValue
value reference: Operations

Time to First Correct Result (learning curve)
type: PropertyValue
value reference: Adoption

Available Built-in Connectors
type: PropertyValue
value reference: Ecosystem

Watermark Support
type: PropertyValue
value reference: Features

Typical Throughput (single node)
type: PropertyValue
value reference: Performance

End-to-End Latency (p99)
type: PropertyValue
value reference: Performance

Delivery Semantics
type: PropertyValue
value reference: Reliability

State Size Capacity
type: PropertyValue
value reference: Scalability

Processing Latency (end-to-end)
type: PropertyValue
value reference: Performance

Processing Semantics
type: PropertyValue
value reference: Reliability

Time Window Support
type: PropertyValue
value reference: Features

Setup Complexity (1-10)
type: PropertyValue
value reference: Ease of Use

Deployment Complexity
type: PropertyValue
value reference: Operations

Time to First Production Deployment
type: PropertyValue
value reference: Implementation

Minimum Memory Requirement
type: PropertyValue
value reference: Resources

Production Deployments Reported
type: PropertyValue
value reference: Adoption

Programming Languages Supported
type: PropertyValue
value reference: Features

First Release Year
type: PropertyValue
value reference: Maturity

Latency (p99 for simple aggregations)
type: PropertyValue
value reference: Performance

Maximum Managed State Size
type: PropertyValue
value reference: Scalability

GitHub Stars (as of 2026)
type: PropertyValue
value reference: Community Adoption

GitHub Stars (2026)
type: PropertyValue
value reference: Community

Job Market Demand
type: PropertyValue
value reference: Employment

Baseline JVM Memory Overhead
type: PropertyValue
value reference: Resource Efficiency

Machine Learning Capabilities
type: PropertyValue
value reference: Analytics

Top-Level Apache Status
type: PropertyValue
value reference: Project Maturity

Average Query Execution (1GB dataset)
type: PropertyValue
value reference: Performance

Maximum Throughput per Node
type: PropertyValue
value reference: Performance

Python Support Level
type: PropertyValue
value reference: Language Support

State Consistency Guarantee
type: PropertyValue
value reference: Data Reliability

Integrated Web UI
type: PropertyValue
value reference: Monitoring

Minimum Java Version Required
type: PropertyValue
value reference: Requirements

Native Connectors Available
type: PropertyValue
value reference: Ecosystem

Memory Overhead (per task)
type: PropertyValue
value reference: Performance

Supported Event Time Semantics
type: PropertyValue
value reference: Features

Throughput (events/sec per node)
type: PropertyValue
value reference: Performance

Batch+Stream Unified Code
type: PropertyValue
value reference: Features

Initial Release Year
type: PropertyValue
value reference: Maturity

Primary Implementation Language
type: PropertyValue
value reference: Architecture

Memory Overhead (idle cluster)
type: PropertyValue
value reference: Resource Efficiency

Time to Build First Pipeline
type: PropertyValue
value reference: Developer Experience

Active Contributors (6-month window)
type: PropertyValue
value reference: Community

Built-in State Backends
type: PropertyValue
value reference: Features

Price (Self-Hosted)
type: PropertyValue
value reference: Cost

Community GitHub Stars
type: PropertyValue
value reference: Community

Years in Production
type: PropertyValue
value reference: Maturity

Built-in Connectors
type: PropertyValue
value reference: Ecosystem

Max Throughput (Typical Setup)
type: PropertyValue
value reference: Performance

Event Latency (Processing End-to-End)
type: PropertyValue
value reference: Performance

Memory Per Node
type: PropertyValue
value reference: Resource Efficiency

Developer Community Size
type: PropertyValue
value reference: Support

Available Libraries & Integrations
type: PropertyValue
value reference: Ecosystem

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 (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

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

Configuration Complexity
type: PropertyValue
value reference: Operational