Hadoop vs Apache Flink
type: Article
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
date published: 2026-07-09T17:30:42.592Z
date created: 2026-07-09T17:30:42.592Z
date modified: 2026-07-09T17:30:42.631Z
content reference time: 2026-07-09T17:30:42.631Z
author: A Versus B
publisher: A Versus B
about: Apache Hadoop
about: Apache Flink
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.
text: Processing Model. Latency. State Management. Memory Efficiency. Ecosystem Maturity. Community Size. Use Case Fit
conclusion 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.
additional property: Total Cost of Ownership (5 years, 100TB)
  type: PropertyValue
  value: Apache Hadoop: $1,200,000-$1,800,000 | Apache Flink: N/A
additional property: Setup Time
  type: PropertyValue
  value: Apache Hadoop: 28-84 days | Apache Flink: N/A
additional property: Required IT Staff (FTE)
  type: PropertyValue
  value: Apache Hadoop: 5-10 FTE | Apache Flink: N/A
additional property: Data Access Latency
  type: PropertyValue
  value: Apache Hadoop: 20-50 ms | Apache Flink: N/A
additional property: Scalability Limit
  type: PropertyValue
  value: Apache Hadoop: Limited by cluster (typically 10-100 PB) | Apache Flink: N/A
additional property: Scale-Up Time
  type: PropertyValue
  value: Apache Hadoop: 24-72 hours | Apache Flink: N/A
additional property: Availability SLA
  type: PropertyValue
  value: Apache Hadoop: 95-99% (cluster-dependent) | Apache Flink: N/A
additional property: Storage Cost (monthly, 100TB)
  type: PropertyValue
  value: Apache Hadoop: $12,500-$25,000 | Apache Flink: N/A
additional property: Processing Latency
  type: PropertyValue
  value: Apache Hadoop: 300-1800 seconds (5-30 minutes) | Apache Flink: 100-500 milliseconds
  value reference: Apache Flink
additional property: Throughput (Records/Second)
  type: PropertyValue
  value: Apache Hadoop: 100K-500K | Apache Flink: 1M-10M
  value reference: Apache Flink
additional property: Memory Usage per Node
  type: PropertyValue
  value: Apache Hadoop: 8-32 GB | Apache Flink: 4-16 GB
  value reference: Apache Flink
additional property: Supported Languages
  type: PropertyValue
  value: Apache Hadoop: 2 (Java, Scala) | Apache Flink: 4 (Java, Scala, Python, SQL)
  value reference: Apache Flink
additional property: Fault Tolerance Mechanism
  type: PropertyValue
  value: Apache Hadoop: Task re-execution + HDFS replication | Apache Flink: Distributed snapshots + checkpointing
additional property: GitHub Stars (2025)
  type: PropertyValue
  value: Apache Hadoop: 12.4K | Apache Flink: 23.8K
  value reference: Apache Flink
additional property: Optimal Dataset Size
  type: PropertyValue
  value: Apache Hadoop: 100+ GB batches | Apache Flink: Continuous streams (any size)
additional property: Processing Speed (Same 1TB dataset)
  type: PropertyValue
  value: Apache Hadoop: 300-600 seconds (disk-based) | Apache Flink: N/A
additional property: Initial Setup Time to Production
  type: PropertyValue
  value: Apache Hadoop: 8-12 weeks | Apache Flink: N/A
additional property: Processing Speed vs MapReduce Baseline
  type: PropertyValue
  value: Apache Hadoop: 1x (baseline) | Apache Flink: N/A
additional property: Monthly Cost (100GB monthly data ingestion, 1,000 compute hours)
  type: PropertyValue
  value: Apache Hadoop: $2,500-5,000 (infrastructure only) | Apache Flink: N/A
additional property: Required Team Skills (FTE equivalents for operations)
  type: PropertyValue
  value: Apache Hadoop: 2-3 dedicated engineers | Apache Flink: N/A
additional property: SQL Query Standards Compliance
  type: PropertyValue
  value: Apache Hadoop: Hive SQL (65% ANSI) | Apache Flink: N/A
additional property: Query Latency (median, standard ETL workload)
  type: PropertyValue
  value: Apache Hadoop: 45-120 seconds | Apache Flink: N/A
additional property: Built-in Collaboration Tools (notebooks, dashboards, repos)
  type: PropertyValue
  value: Apache Hadoop: 0 (requires third-party) | Apache Flink: N/A
additional property: Time to Query 1TB Dataset
  type: PropertyValue
  value: Apache Hadoop: 10-30 seconds (with Spark) | Apache Flink: N/A
additional property: Infrastructure Cost (Annual, 50TB dataset)
  type: PropertyValue
  value: Apache Hadoop: $150,000-$250,000 | Apache Flink: N/A
additional property: Infrastructure Cost (Annual, 500TB dataset)
  type: PropertyValue
  value: Apache Hadoop: $200,000-$400,000 | Apache Flink: N/A
additional property: Setup Time to First Query
  type: PropertyValue
  value: Apache Hadoop: 30-90 days (cluster + network + security) | Apache Flink: N/A
additional property: Maximum Unstructured Data Support
  type: PropertyValue
  value: Apache Hadoop: 90% (native HDFS support for any file type) | Apache Flink: N/A
additional property: Admin/DevOps Time Required (Monthly)
  type: PropertyValue
  value: Apache Hadoop: 40-80 hours (patching, monitoring, scaling) | Apache Flink: N/A
additional property: Data Residency Control
  type: PropertyValue
  value: Apache Hadoop: Complete (on-premises or self-managed cloud) | Apache Flink: N/A
additional property: Maximum Query Parallelism
  type: PropertyValue
  value: Apache Hadoop: 10,000+ (custom hardware limits) | Apache Flink: N/A
additional property: Processing Speed (Average Query)
  type: PropertyValue
  value: Apache Hadoop: 300-600 seconds | Apache Flink: N/A
additional property: Memory Requirement (Per Node)
  type: PropertyValue
  value: Apache Hadoop: 4-8 GB | Apache Flink: N/A
additional property: First Release
  type: PropertyValue
  value: Apache Hadoop: 2011 | Apache Flink: N/A
additional property: Supported Programming Languages
  type: PropertyValue
  value: Apache Hadoop: 5 languages (Java, Python, Scala, C++, Ruby) | Apache Flink: 4 languages (Java, Scala, Python, SQL)
  value reference: Apache Hadoop
additional property: Real-time Streaming Capability
  type: PropertyValue
  value: Apache Hadoop: Not supported | Apache Flink: N/A
additional property: Market Adoption by Fortune 500
  type: PropertyValue
  value: Apache Hadoop: 35% | Apache Flink: N/A
additional property: Typical Cluster Cost (100-node setup)
  type: PropertyValue
  value: Apache Hadoop: $180,000-250,000 | Apache Flink: N/A
additional property: Fault Tolerance Method
  type: PropertyValue
  value: Apache Hadoop: Replication (3x copies) | Apache Flink: N/A
additional property: Initial Setup Time
  type: PropertyValue
  value: Apache Hadoop: 3 weeks | Apache Flink: N/A
additional property: Query Latency (1TB scan)
  type: PropertyValue
  value: Apache Hadoop: 120-300 seconds | Apache Flink: N/A
additional property: Total Cost of Ownership (100TB/year)
  type: PropertyValue
  value: Apache Hadoop: $150,000-$400,000 | Apache Flink: N/A
additional property: Team Expertise Required
  type: PropertyValue
  value: Apache Hadoop: 6-12 months | Apache Flink: N/A
additional property: Supported Processing Models
  type: PropertyValue
  value: Apache Hadoop: 4+ (batch, streaming, graph, ML) | Apache Flink: N/A
additional property: Data Storage Capacity
  type: PropertyValue
  value: Apache Hadoop: Unlimited (cluster-dependent) | Apache Flink: N/A
additional property: Vendor Lock-in Risk
  type: PropertyValue
  value: Apache Hadoop: Low (portable open-source) | Apache Flink: N/A
additional property: Initial Deployment Time
  type: PropertyValue
  value: Apache Hadoop: 4-8 weeks | Apache Flink: N/A
additional property: Processing Speed (Iterative ML)
  type: PropertyValue
  value: Apache Hadoop: 1x (MapReduce baseline) | Apache Flink: N/A
additional property: SQL Query Latency (100GB dataset)
  type: PropertyValue
  value: Apache Hadoop: 15-45 seconds (Hive) | Apache Flink: N/A
interactivity type: active
significant link: https://www.aversusb.net/entity/apache-hadoop
significant link: https://www.aversusb.net/alternatives/apache-hadoop
significant link: https://www.aversusb.net/entity/apache-flink
significant link: https://www.aversusb.net/alternatives/apache-flink
significant link: https://www.aversusb.net/api/answer/hadoop-vs-flink)
significant link: https://www.aversusb.net/api/v1/schema/hadoop-vs-flink)
related link: https://www.aversusb.net/compare/hadoop-vs-flink
related link: https://www.aversusb.net/compare/flink-vs-kafka
related link: https://www.aversusb.net/compare/flink-vs-apache-storm
related link: https://www.aversusb.net/compare/hadoop-vs-snowflake
related link: https://www.aversusb.net/compare/hadoop-vs-aws-s3
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
teaches: How to choose between Apache Hadoop and Apache Flink
genre: Software

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caption: Hadoop vs Apache Flink — Side-by-side comparison on A Versus B

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

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: Hadoop vs Apache Flink
image: ImageObject
  caption: Apache Flink

Hadoop vs Apache Flink — Structured Comparison Data
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description: Machine-readable comparison dataset for Hadoop vs Apache Flink. Contains 164 attribute comparisons, 5 FAQ pairs.
language: en-US
license: https://creativecommons.org/licenses/by/4.0/
creator: A Versus B
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variable measured: Required DevOps Team Size
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is based on: https://www.aversusb.net/compare/hadoop-vs-flink)

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: User 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: Developer Experience
has defined term: Capability
has defined term: Compliance
has defined term: Infrastructure
has defined term: History
has defined term: Industry
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
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: Industry Adoption
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: Compatibility
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

User Experience
type: DefinedTerm
term code: user-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

Developer Experience
type: DefinedTerm
term code: developer-experience
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

Industry
type: DefinedTerm
term code: industry
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
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

Industry Adoption
type: DefinedTerm
term code: industry-adoption
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

Compatibility
type: DefinedTerm
term code: compatibility
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-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

How to Choose Between Apache Hadoop and Apache Flink
type: HowTo
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
total time: PT3M
step: Consider: Processing Model
step: Consider: Latency
step: Consider: State Management
step: Consider: Memory Efficiency
step: Consider: Ecosystem Maturity
step: Consider: Community Size
step: Consider: Use Case Fit
tool: A Versus B Comparison Guide
tip: HowToTip
  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.

Consider: Processing Model
type: HowToStep
position: 1
text: Processing Model: Apache Hadoop has Batch processing only, while Apache Flink has Stream and batch processing.

Consider: Latency
type: HowToStep
position: 2
text: Latency: Apache Hadoop has Minutes to hours, while Apache Flink has Milliseconds to seconds.

Consider: State Management
type: HowToStep
position: 3
text: State Management: Apache Hadoop has Limited, external storage required, while Apache Flink has Native, in-memory state backend.

Consider: Memory Efficiency
type: HowToStep
position: 4
text: Memory Efficiency: Apache Hadoop has Disk-based, slower I/O, while Apache Flink has In-memory processing, faster.

Consider: Ecosystem Maturity
type: HowToStep
position: 5
text: Ecosystem Maturity: Apache Hadoop has 15+ years, extensive integrations, while Apache Flink has 10+ years, growing integrations.

Consider: Community Size
type: HowToStep
position: 6
text: Community Size: Apache Hadoop has ~30,000+ commits on GitHub, while Apache Flink has ~25,000+ commits on GitHub.

Consider: Use Case Fit
type: HowToStep
position: 7
text: Use Case Fit: Apache Hadoop has Historical data analysis, ETL, while Apache Flink has Real-time analytics, CEP, fraud detection.

claimreview
type: ClaimReview
is accessible for free: true
conditions of access: Free
claim reviewed: Hadoop vs Apache Flink
review body: 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.
review rating: Rating
  rating: 5
  worst rating: 1
  best rating: 5
  alternate name: Verified Comparison
author: A Versus B
item reviewed: Hadoop vs Apache Flink

Annual Cost (100TB/year, 5-node baseline)
type: PropertyValue
value: Apache Hadoop: $180,000-$250,000 | Apache Flink: N/A

Native Row/Column-Level Access Control
type: PropertyValue
value: Apache Hadoop: No (requires Ranger) | Apache Flink: N/A

Cluster Auto-scaling Capability
type: PropertyValue
value: Apache Hadoop: Manual (requires YARN configuration) | Apache Flink: N/A

Collaborative Notebooks with Version Control
type: PropertyValue
value: Apache Hadoop: No (requires Jupyter/Git separately) | Apache Flink: N/A

On-Premises Deployment Option
type: PropertyValue
value: Apache Hadoop: Yes (full control) | Apache Flink: N/A

Query Performance (1TB dataset)
type: PropertyValue
value: Apache Hadoop: 120-300 seconds | Apache Flink: N/A

Annual TCO (100TB workload)
type: PropertyValue
value: Apache Hadoop: $150,000-$300,000 | Apache Flink: N/A

Minimum Team Size
type: PropertyValue
value: Apache Hadoop: 4-8 (DevOps, engineers, admins) | Apache Flink: N/A

Maximum Query Concurrency
type: PropertyValue
value: Apache Hadoop: 50-100 per cluster | Apache Flink: N/A

Storage Cost (per TB/month)
type: PropertyValue
value: Apache Hadoop: $12-20 | Apache Flink: N/A

Data Locality Advantage
type: PropertyValue
value: Apache Hadoop: 40-60% reduction in network I/O | Apache Flink: N/A

Custom Algorithm Support (1-5 scale)
type: PropertyValue
value: Apache Hadoop: 5 (full MapReduce/Spark) | Apache Flink: N/A

Query Performance (10TB TPC-DS benchmark)
type: PropertyValue
value: Apache Hadoop: 95 seconds | Apache Flink: N/A

Annual Cost (100TB, 24/7 usage)
type: PropertyValue
value: Apache Hadoop: $120,000 | Apache Flink: N/A

Compute & Storage Coupling
type: PropertyValue
value: Apache Hadoop: Tightly coupled (scale together) | Apache Flink: N/A

SQL Query Support
type: PropertyValue
value: Apache Hadoop: Hive SQL (SQL92, limited optimizations) | Apache Flink: N/A

Data Recovery (Time Travel)
type: PropertyValue
value: Apache Hadoop: Manual snapshots only | Apache Flink: N/A

Required DevOps Team Size
type: PropertyValue
value: Apache Hadoop: 3-5 engineers | Apache Flink: N/A

Community Size (GitHub Stars)
type: PropertyValue
value: Apache Hadoop: 14,200 stars | Apache Flink: N/A

Throughput Capacity
type: PropertyValue
value: Apache Hadoop: 1M-10M per node | Apache Flink: 1M-100M per node
value reference: Apache Flink

Memory Usage per Task
type: PropertyValue
value: Apache Hadoop: 500-2000 MB | Apache Flink: 100-800 MB
value reference: Apache Flink

Project Age
type: PropertyValue
value: Apache Hadoop: 15 years (since 2006) | Apache Flink: 10 years (since 2014)
value reference: Apache Hadoop

GitHub Stars
type: PropertyValue
value: Apache Hadoop: 14,500+ stars | Apache Flink: 23,500+ stars
value reference: Apache Flink

State Backend Options
type: PropertyValue
value: Apache Hadoop: External solutions required (HBase, etc.) | Apache Flink: RocksDB (100GB+), HashMap, External KV stores

Minimum Cluster Size
type: PropertyValue
value: Apache Hadoop: 3 nodes recommended | Apache Flink: 1-2 nodes viable
value reference: Apache Flink

Minimum Operational Complexity
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 5-7 (JobManager, TaskManagers, StateBackend, Checkpoints)

Time to First Correct Result (learning curve)
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 6-10

Available Built-in Connectors
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 50+

Watermark Support
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: Yes (core feature)

Typical Throughput (single node)
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 250,000

End-to-End Latency (p99)
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 5-50ms

Delivery Semantics
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: Exactly-once (native)

State Size Capacity
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 500+

Processing Latency (end-to-end)
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 50-100ms

Processing Semantics
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: Exactly-once

Time Window Support
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: Event-time, processing-time, session windows, custom

Setup Complexity (1-10)
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 7/10

Deployment Complexity
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: Requires cluster with YARN/Kubernetes, moderate DevOps

Time to First Production Deployment
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 8-12 weeks (with Kubernetes ops experience)

Minimum Memory Requirement
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 1024 MB

Production Deployments Reported
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 10,000+

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

First Release Year
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 2011

Latency (p99 for simple aggregations)
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 100-500 ms (tuning dependent)

Maximum Managed State Size
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: Terabyte-scale (tested to 10+ TB)

GitHub Stars (as of 2026)
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 29,000+

GitHub Stars (2026)
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 23,800+

Job Market Demand
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: ~1,850

Baseline JVM Memory Overhead
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 1.5-2.5 GB

Machine Learning Capabilities
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: Limited (requires external libraries)

Top-Level Apache Status
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 2015

Average Query Execution (1GB dataset)
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 2-3 seconds (streaming) / 4-6 (batch)

Maximum Throughput per Node
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 100,000-1,000,000 events/sec

Python Support Level
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: PyFlink added in v1.11 (2020); improved in v1.14+

State Consistency Guarantee
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: Exactly-once (configurable per checkpoint)

Integrated Web UI
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: Basic REST API only (external UI required)

Minimum Java Version Required
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: Java 11+

Native Connectors Available
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: ~30 native connectors

Memory Overhead (per task)
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: ~200-400MB (optimized)

Supported Event Time Semantics
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: Full with watermarks, out-of-order handling, allowedLateness

Throughput (events/sec per node)
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: ~1-2M events/sec

Batch+Stream Unified Code
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: Separate APIs (DataStream vs Batch)

Initial Release Year
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 2014

Primary Implementation Language
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: Java

Memory Overhead (idle cluster)
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 2-4 GB

Time to Build First Pipeline
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 72

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

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

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

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

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

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

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

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

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

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

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

Enterprise Adoption Rate
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 18% (Alibaba, Netflix, Uber, Lyft use cases)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Maximum Throughput
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: Millions (100M+ with tuning)

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

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

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

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

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

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

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

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

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

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

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

Processing Latency (p99)
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 50-100ms

Throughput Per Node
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 10,000,000

Exactly-Once Semantics
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: Native with distributed snapshots

Event-Time Support
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: Full support with watermarks and allowed lateness

Minimum Memory Per Worker
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 2-4

GitHub Stars (Last 12 Months)
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 2000+

Configuration Complexity
type: PropertyValue
value: Apache Hadoop: N/A | Apache Flink: 60+ core parameters

SpeakableSpecification
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Apache Hadoop — Wikipedia
type: CreativeWork

Apache Flink — Wikipedia
type: CreativeWork

Compare Apache Hadoop vs Apache Flink
type: Action
additional type: CompareAction
target: https://www.aversusb.net/compare/hadoop-vs-flink)
object: Apache Hadoop
object: Apache Flink

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: 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: History

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: Community

Available Libraries & Integrations
type: PropertyValue
value reference: Ecosystem

Enterprise Adoption Rate
type: PropertyValue
value reference: Industry Adoption

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: Features

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