Hadoop vs BigQuery
type: Article
description: Hadoop is a self-managed, open-source distributed computing framework requiring significant infrastructure investment, while BigQuery is a fully managed, serverless cloud data warehouse with pay-as-you-go pricing. Hadoop suits organizations with existing data centers and complex custom workflows, whereas BigQuery excels for rapid analytics without operational overhead.
language: en-US
date published: 2026-07-08T23:24:31.705Z
date created: 2026-07-08T23:24:31.705Z
date modified: 2026-07-08T23:24:31.740Z
content reference time: 2026-07-08T23:24:31.740Z
author: A Versus B
publisher: A Versus B
about: Apache Hadoop
about: Google BigQuery
abstract: Hadoop is a self-managed, open-source distributed computing framework requiring significant infrastructure investment, while BigQuery is a fully managed, serverless cloud data warehouse with pay-as-you-go pricing. Hadoop suits organizations with existing data centers and complex custom workflows, whereas BigQuery excels for rapid analytics without operational overhead.
text: Deployment Model. Setup & Maintenance Time. Query Speed (1TB scan). Total Cost of Ownership (annual, 100TB). Learning Curve. Data Locality Optimization. Custom Algorithm Support
conclusion text: Choose Hadoop if you have existing on-premises infrastructure, need maximum customization for complex algorithms, have strict data residency requirements, or process data with highly variable workloads where you can optimize cluster utilization. Choose BigQuery if you prioritize fast time-to-insight, want zero operational overhead, need automatic scaling, have budget for managed services, or run standard analytical queries with predictable patterns.
additional property: Total Cost of Ownership (5 years, 100TB)
  type: PropertyValue
  value: Apache Hadoop: $1,200,000-$1,800,000 | Google BigQuery: N/A
additional property: Setup Time
  type: PropertyValue
  value: Apache Hadoop: 28-84 days | Google BigQuery: N/A
additional property: Required IT Staff (FTE)
  type: PropertyValue
  value: Apache Hadoop: 5-10 FTE | Google BigQuery: N/A
additional property: Data Access Latency
  type: PropertyValue
  value: Apache Hadoop: 20-50 ms | Google BigQuery: N/A
additional property: Scalability Limit
  type: PropertyValue
  value: Apache Hadoop: Limited by cluster (typically 10-100 PB) | Google BigQuery: N/A
additional property: Scale-Up Time
  type: PropertyValue
  value: Apache Hadoop: 24-72 hours | Google BigQuery: N/A
additional property: Availability SLA
  type: PropertyValue
  value: Apache Hadoop: 95-99% (cluster-dependent) | Google BigQuery: N/A
additional property: Storage Cost (monthly, 100TB)
  type: PropertyValue
  value: Apache Hadoop: $12,500-$25,000 | Google BigQuery: N/A
additional property: Processing Latency
  type: PropertyValue
  value: Apache Hadoop: 180-3600 seconds | Google BigQuery: N/A
additional property: Throughput (Records/Second)
  type: PropertyValue
  value: Apache Hadoop: 100K-500K | Google BigQuery: N/A
additional property: Memory Usage per Node
  type: PropertyValue
  value: Apache Hadoop: 8-32 GB | Google BigQuery: N/A
additional property: Minimum Cluster Size
  type: PropertyValue
  value: Apache Hadoop: 3-5 nodes | Google BigQuery: N/A
additional property: Supported Languages
  type: PropertyValue
  value: Apache Hadoop: 2 (Java, Scala) | Google BigQuery: N/A
additional property: Fault Tolerance Mechanism
  type: PropertyValue
  value: Apache Hadoop: Task re-execution + HDFS replication | Google BigQuery: N/A
additional property: GitHub Stars (2025)
  type: PropertyValue
  value: Apache Hadoop: 12.4K | Google BigQuery: N/A
additional property: Optimal Dataset Size
  type: PropertyValue
  value: Apache Hadoop: 100+ GB batches | Google BigQuery: N/A
additional property: Processing Speed (Same 1TB dataset)
  type: PropertyValue
  value: Apache Hadoop: 300-600 seconds (disk-based) | Google BigQuery: N/A
additional property: Initial Setup Time to Production
  type: PropertyValue
  value: Apache Hadoop: 8-12 weeks | Google BigQuery: N/A
additional property: Processing Speed vs MapReduce Baseline
  type: PropertyValue
  value: Apache Hadoop: 1x (baseline) | Google BigQuery: 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) | Google BigQuery: N/A
additional property: Required Team Skills (FTE equivalents for operations)
  type: PropertyValue
  value: Apache Hadoop: 2-3 dedicated engineers | Google BigQuery: N/A
additional property: SQL Query Standards Compliance
  type: PropertyValue
  value: Apache Hadoop: Hive SQL (65% ANSI) | Google BigQuery: N/A
additional property: Query Latency (median, standard ETL workload)
  type: PropertyValue
  value: Apache Hadoop: 45-120 seconds | Google BigQuery: N/A
additional property: Built-in Collaboration Tools (notebooks, dashboards, repos)
  type: PropertyValue
  value: Apache Hadoop: 0 (requires third-party) | Google BigQuery: N/A
additional property: Community Size (GitHub Stars)
  type: PropertyValue
  value: Apache Hadoop: 13,500 stars (hadoop/hadoop) | Google BigQuery: N/A
additional property: Time to Query 1TB Dataset
  type: PropertyValue
  value: Apache Hadoop: 10-30 seconds (with Spark) | Google BigQuery: 5-15 seconds
  value reference: Google BigQuery
additional property: Infrastructure Cost (Annual, 50TB dataset)
  type: PropertyValue
  value: Apache Hadoop: $150,000-$250,000 | Google BigQuery: $18,750 ($6.25/TB × 50TB × 12 months)
  value reference: Google BigQuery
additional property: Infrastructure Cost (Annual, 500TB dataset)
  type: PropertyValue
  value: Apache Hadoop: $200,000-$400,000 | Google BigQuery: $187,500 ($6.25/TB × 500TB × 12 months)
  value reference: Google BigQuery
additional property: Setup Time to First Query
  type: PropertyValue
  value: Apache Hadoop: 30-90 days (cluster + network + security) | Google BigQuery: 1-2 days (account + dataset creation)
  value reference: Google BigQuery
additional property: Maximum Unstructured Data Support
  type: PropertyValue
  value: Apache Hadoop: 90% (native HDFS support for any file type) | Google BigQuery: 30% (requires Dataflow for preprocessing)
  value reference: Apache Hadoop
additional property: Admin/DevOps Time Required (Monthly)
  type: PropertyValue
  value: Apache Hadoop: 40-80 hours (patching, monitoring, scaling) | Google BigQuery: 2-4 hours (monitoring queries, access control)
  value reference: Google BigQuery
additional property: Data Residency Control
  type: PropertyValue
  value: Apache Hadoop: Complete (on-premises or self-managed cloud) | Google BigQuery: Google Cloud region-level only
additional property: Maximum Query Parallelism
  type: PropertyValue
  value: Apache Hadoop: 10,000+ (custom hardware limits) | Google BigQuery: Unlimited (transparent to user)
additional property: Processing Speed (Average Query)
  type: PropertyValue
  value: Apache Hadoop: 300-600 seconds | Google BigQuery: N/A
additional property: Memory Requirement (Per Node)
  type: PropertyValue
  value: Apache Hadoop: 4-8 GB | Google BigQuery: N/A
additional property: First Release
  type: PropertyValue
  value: Apache Hadoop: 2011 | Google BigQuery: N/A
additional property: Supported Programming Languages
  type: PropertyValue
  value: Apache Hadoop: Java, Scala | Google BigQuery: N/A
additional property: Real-time Streaming Capability
  type: PropertyValue
  value: Apache Hadoop: Not supported | Google BigQuery: N/A
additional property: Market Adoption by Fortune 500
  type: PropertyValue
  value: Apache Hadoop: 35% | Google BigQuery: N/A
additional property: Typical Cluster Cost (100-node setup)
  type: PropertyValue
  value: Apache Hadoop: $180,000-250,000 | Google BigQuery: N/A
additional property: Fault Tolerance Method
  type: PropertyValue
  value: Apache Hadoop: Replication (3x copies) | Google BigQuery: N/A
additional property: Initial Setup Time
  type: PropertyValue
  value: Apache Hadoop: 4-12 weeks | Google BigQuery: 0.5-1 week
  value reference: Google BigQuery
additional property: Query Latency (1TB scan)
  type: PropertyValue
  value: Apache Hadoop: 120-300 seconds | Google BigQuery: 15-45 seconds
  value reference: Google BigQuery
additional property: Total Cost of Ownership (100TB/year)
  type: PropertyValue
  value: Apache Hadoop: $150,000-$400,000 | Google BigQuery: $25,000-$60,000
  value reference: Google BigQuery
additional property: Team Expertise Required
  type: PropertyValue
  value: Apache Hadoop: 6-12 months | Google BigQuery: 2-4 weeks
  value reference: Google BigQuery
additional property: Supported Processing Models
  type: PropertyValue
  value: Apache Hadoop: 4+ (batch, streaming, graph, ML) | Google BigQuery: 2 (SQL, streaming via Pub/Sub)
  value reference: Apache Hadoop
additional property: Data Storage Capacity
  type: PropertyValue
  value: Apache Hadoop: Unlimited (cluster-dependent) | Google BigQuery: Unlimited (cloud-based)
additional property: Vendor Lock-in Risk
  type: PropertyValue
  value: Apache Hadoop: Low (portable open-source) | Google BigQuery: N/A
additional property: Initial Deployment Time
  type: PropertyValue
  value: Apache Hadoop: 4-8 weeks | Google BigQuery: 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/google-bigquery
significant link: https://www.aversusb.net/alternatives/google-bigquery
significant link: https://www.aversusb.net/api/answer/hadoop-vs-bigquery)
significant link: https://www.aversusb.net/api/v1/schema/hadoop-vs-bigquery)
related link: https://www.aversusb.net/compare/hadoop-vs-bigquery
related link: https://www.aversusb.net/compare/hadoop-vs-flink
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/apache-spark-vs-bigquery
related link: https://www.aversusb.net/compare/bigquery-vs-pinot
related link: https://www.aversusb.net/compare/druid-vs-bigquery
related link: https://www.aversusb.net/compare/hadoop-vs-databricks
teaches: How to choose between Apache Hadoop and Google BigQuery
genre: Software

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

A Versus B
type: Organization

Apache Hadoop
type: SoftwareApplication
alternate name: AH
language: en-US
description: Open-source distributed computing framework for processing large datasets across commodity hardware clusters.
subject of: Hadoop vs BigQuery

Google BigQuery
type: SoftwareApplication
alternate name: GB
alternate name: Google Bigquery
language: en-US
description: Fully managed, serverless cloud data warehouse offering unlimited scalability with standard SQL and real-time analytics.
subject of: Hadoop vs BigQuery

Hadoop vs BigQuery — Structured Comparison Data
type: Dataset
description: Machine-readable comparison dataset for Hadoop vs BigQuery. Contains 94 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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distribution: Structured FAQ pairs JSON
  type: DataDownload
  encoding format: application/json
distribution: AI Answer API (citation-ready)
  type: DataDownload
  encoding format: application/json
distribution: Related comparisons JSON
  type: DataDownload
  encoding format: application/json
variable measured: Total Cost of Ownership (5 years, 100TB)
  type: PropertyValue
  value reference: Cost
variable measured: Setup Time
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  value reference: Deployment
variable measured: Required IT Staff (FTE)
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  value reference: Operations
variable measured: Data Access Latency
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  value reference: Performance
variable measured: Scalability Limit
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  value reference: Capacity
variable measured: Scale-Up Time
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variable measured: Availability SLA
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  value reference: Reliability
variable measured: Storage Cost (monthly, 100TB)
  type: PropertyValue
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variable measured: Processing Latency
  type: PropertyValue
  value reference: Performance
variable measured: Throughput (Records/Second)
  type: PropertyValue
  value reference: Performance
variable measured: Memory Usage per Node
  type: PropertyValue
  value reference: Resource Efficiency
variable measured: Minimum Cluster Size
  type: PropertyValue
  value reference: Infrastructure
variable measured: Supported Languages
  type: PropertyValue
  value reference: Localization
variable measured: Fault Tolerance Mechanism
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  value reference: Reliability
variable measured: GitHub Stars (2025)
  type: PropertyValue
  value reference: Community
variable measured: Optimal Dataset Size
  type: PropertyValue
  value reference: Use Case
variable measured: Processing Speed (Same 1TB dataset)
  type: PropertyValue
  value reference: Performance
variable measured: Initial Setup Time to Production
  type: PropertyValue
  value reference: Deployment
variable measured: Processing Speed vs MapReduce Baseline
  type: PropertyValue
  value reference: Performance
variable measured: Monthly Cost (100GB monthly data ingestion, 1,000 compute hours)
  type: PropertyValue
  value reference: Pricing
variable measured: Required Team Skills (FTE equivalents for operations)
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variable measured: SQL Query Standards Compliance
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variable measured: Query Latency (median, standard ETL workload)
  type: PropertyValue
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variable measured: Built-in Collaboration Tools (notebooks, dashboards, repos)
  type: PropertyValue
  value reference: Features
variable measured: Community Size (GitHub Stars)
  type: PropertyValue
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variable measured: Time to Query 1TB Dataset
  type: PropertyValue
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variable measured: Infrastructure Cost (Annual, 50TB dataset)
  type: PropertyValue
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variable measured: Infrastructure Cost (Annual, 500TB dataset)
  type: PropertyValue
  value reference: Cost
variable measured: Setup Time to First Query
  type: PropertyValue
  value reference: Ease of Use
variable measured: Maximum Unstructured Data Support
  type: PropertyValue
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variable measured: Admin/DevOps Time Required (Monthly)
  type: PropertyValue
  value reference: Operations
variable measured: Data Residency Control
  type: PropertyValue
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variable measured: Maximum Query Parallelism
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variable measured: Processing Speed (Average Query)
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variable measured: Memory Requirement (Per Node)
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variable measured: First Release
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variable measured: Supported Programming Languages
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variable measured: Real-time Streaming Capability
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variable measured: Market Adoption by Fortune 500
  type: PropertyValue
  value reference: Industry
variable measured: Typical Cluster Cost (100-node setup)
  type: PropertyValue
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variable measured: Fault Tolerance Method
  type: PropertyValue
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variable measured: Initial Setup Time
  type: PropertyValue
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variable measured: Query Latency (1TB scan)
  type: PropertyValue
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variable measured: Total Cost of Ownership (100TB/year)
  type: PropertyValue
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variable measured: Team Expertise Required
  type: PropertyValue
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variable measured: Supported Processing Models
  type: PropertyValue
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variable measured: Data Storage Capacity
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variable measured: Vendor Lock-in Risk
  type: PropertyValue
  value reference: Flexibility
variable measured: Initial Deployment Time
  type: PropertyValue
  value reference: Implementation
variable measured: Processing Speed (Iterative ML)
  type: PropertyValue
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variable measured: SQL Query Latency (100GB dataset)
  type: PropertyValue
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variable measured: Annual Cost (100TB/year, 5-node baseline)
  type: PropertyValue
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variable measured: Native Row/Column-Level Access Control
  type: PropertyValue
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variable measured: Cluster Auto-scaling Capability
  type: PropertyValue
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variable measured: Collaborative Notebooks with Version Control
  type: PropertyValue
  value reference: Collaboration
variable measured: On-Premises Deployment Option
  type: PropertyValue
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variable measured: Query Performance (1TB dataset)
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variable measured: Annual TCO (100TB workload)
  type: PropertyValue
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variable measured: Minimum Team Size
  type: PropertyValue
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variable measured: Maximum Query Concurrency
  type: PropertyValue
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variable measured: Storage Cost (per TB/month)
variable measured: Data Locality Advantage
variable measured: Custom Algorithm Support (1-5 scale)
variable measured: Query Performance on 1TB Dataset
variable measured: Cluster Setup Time
variable measured: Cost per Core-Hour
variable measured: Machine Learning Algorithms Available
variable measured: Supported Languages/APIs
variable measured: Maximum Dataset Size Supported
is based on: https://www.aversusb.net/compare/hadoop-vs-bigquery)

Hadoop vs BigQuery — Attribute Category Vocabulary
type: DefinedTermSet
language: en-US
description: Taxonomy of attribute categories used to classify comparison data for Hadoop vs BigQuery.
has defined term: Cost
has defined term: Deployment
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: Infrastructure
has defined term: Localization
has defined term: Community
has defined term: Use Case
has defined term: Pricing
has defined term: Features
has defined term: Ease of Use
has defined term: Capability
has defined term: Compliance
has defined term: History
has defined term: Industry
has defined term: Flexibility
has defined term: Implementation
has defined term: Governance
has defined term: Collaboration
has defined term: Customization
has defined term: ML Capabilities
has defined term: Compatibility
has defined term: Throughput
has defined term: Total Cost
has defined term: Real-time Capability
has defined term: Time to Value

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

ML Capabilities
type: DefinedTerm
term code: ml-capabilities
in defined term set: Hadoop vs BigQuery — Attribute Category Vocabulary

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

Throughput
type: DefinedTerm
term code: throughput
in defined term set: Hadoop vs BigQuery — Attribute Category Vocabulary

Total Cost
type: DefinedTerm
term code: total-cost
in defined term set: Hadoop vs BigQuery — Attribute Category Vocabulary

Real-time Capability
type: DefinedTerm
term code: real-time-capability
in defined term set: Hadoop vs BigQuery — Attribute Category Vocabulary

Time to Value
type: DefinedTerm
term code: time-to-value
in defined term set: Hadoop vs BigQuery — Attribute Category Vocabulary

faq
type: FAQPage
language: en-US
is accessible for free: true
conditions of access: Free
date modified: 2026-07-08T23:24:31.740Z
author: A Versus B
publisher: A Versus B
is part of: hadoop-vs-bigquery)
main entity: Can I use BigQuery with my existing on-premises data?
  type: Question
  accepted answer: Answer
    text: Yes, but with caveats. BigQuery Omni supports multi-cloud deployment, but data transfer incurs egress costs ($0.12/GB from on-premises). Cloud Storage staging with BigQuery Transfer Service is more economical. Hadoop keeps data local, eliminating network costs entirely—critical for PB-scale datasets.
    language: en-US
main entity: Which is better for machine learning?
  type: Question
  accepted answer: Answer
    text: BigQuery has advantages via native integration with Vertex AI (Google's ML platform) and BigQueryML for in-database model training. Hadoop excels for complex iterative algorithms (e.g., graph processing, custom neural networks) via Spark MLlib. BigQuery wins for standard ML; Hadoop wins for research-grade customization.
    language: en-US
main entity: How do I estimate costs between the two?
  type: Question
  accepted answer: Answer
    text: Hadoop: Calculate hardware ($300k), annual staffing ($300-500k for 4-6 engineers), electricity (~$50k), maintenance. BigQuery: Scan cost ($5-7/TB) × query volume. Example: 1,000 TB scans/month = $5-7k/month ($60-84k/year), plus storage ($7/TB/month × 1,000TB = $84k/year). Break-even is typically 12-18 months for large Hadoop deployments.
    language: en-US
main entity: Can Hadoop match BigQuery's query speed?
  type: Question
  accepted answer: Answer
    text: Not typically. BigQuery uses columnar storage, query optimization, and massive parallelism (1000s of slots). Hadoop with Spark can match it for pre-optimized data, but requires manual tuning. BigQuery's speed advantage comes from architectural design; Hadoop requires heavy optimization effort.
    language: en-US
main entity: What if I need both on-premises AND cloud?
  type: Question
  accepted answer: Answer
    text: Hybrid approaches exist: Run Hadoop on-premises for heavy lifting, then move results to BigQuery for analytics. Alternatively, use Google Cloud's Dataproc (managed Hadoop/Spark) as a middle ground—reduces Hadoop ops overhead but costs more than BigQuery. Evaluate the 70/30 rule: if 70%+ queries are standard SQL, choose BigQuery; if 30%+ need custom algorithms, add Hadoop.
    language: en-US

How to Choose Between Apache Hadoop and Google BigQuery
type: HowTo
description: Hadoop is a self-managed, open-source distributed computing framework requiring significant infrastructure investment, while BigQuery is a fully managed, serverless cloud data warehouse with pay-as-you-go pricing. Hadoop suits organizations with existing data centers and complex custom workflows, whereas BigQuery excels for rapid analytics without operational overhead.
language: en-US
total time: PT3M
step: Consider: Deployment Model
step: Consider: Setup & Maintenance Time
step: Consider: Query Speed (1TB scan)
step: Consider: Total Cost of Ownership (annual, 100TB)
step: Consider: Learning Curve
step: Consider: Data Locality Optimization
step: Consider: Custom Algorithm Support
tool: A Versus B Comparison Guide
tip: HowToTip
  text: Choose Hadoop if you have existing on-premises infrastructure, need maximum customization for complex algorithms, have strict data residency requirements, or process data with highly variable workloads where you can optimize cluster utilization. Choose BigQuery if you prioritize fast time-to-insight, want zero operational overhead, need automatic scaling, have budget for managed services, or run standard analytical queries with predictable patterns.

Consider: Deployment Model
type: HowToStep
position: 1
text: Deployment Model: Apache Hadoop has Self-managed on-premises or cloud VMs, while Google BigQuery has Fully managed serverless (Google Cloud).

Consider: Setup & Maintenance Time
type: HowToStep
position: 2
text: Setup & Maintenance Time: Apache Hadoop has 4-12 weeks for cluster deployment, while Google BigQuery has Minutes to hours.

Consider: Query Speed (1TB scan)
type: HowToStep
position: 3
text: Query Speed (1TB scan): Apache Hadoop has 2-5 minutes typical, while Google BigQuery has 10-30 seconds typical.

Consider: Total Cost of Ownership (annual, 100TB)
type: HowToStep
position: 4
text: Total Cost of Ownership (annual, 100TB): Apache Hadoop has $150,000-$300,000, while Google BigQuery has $50,000-$75,000.

Consider: Learning Curve
type: HowToStep
position: 5
text: Learning Curve: Apache Hadoop has Steep (Java/MapReduce required), while Google BigQuery has Moderate (standard SQL).

Consider: Data Locality Optimization
type: HowToStep
position: 6
text: Data Locality Optimization: Apache Hadoop has Native, built-in advantage, while Google BigQuery has Not applicable (cloud-native).

Consider: Custom Algorithm Support
type: HowToStep
position: 7
text: Custom Algorithm Support: Apache Hadoop has Extensive via MapReduce/Spark, while Google BigQuery has Limited to built-in functions & UDFs.

claimreview
type: ClaimReview
is accessible for free: true
conditions of access: Free
claim reviewed: Hadoop vs BigQuery
review body: Hadoop is a self-managed, open-source distributed computing framework requiring significant infrastructure investment, while BigQuery is a fully managed, serverless cloud data warehouse with pay-as-you-go pricing. Hadoop suits organizations with existing data centers and complex custom workflows, whereas BigQuery excels for rapid analytics without operational overhead.
review rating: Rating
  rating: 5
  worst rating: 1
  best rating: 5
  alternate name: Verified Comparison
author: A Versus B
item reviewed: Hadoop vs BigQuery

Processing Speed (Iterative ML)
type: PropertyValue
value: Apache Hadoop: 1x (MapReduce baseline) | Google BigQuery: N/A

SQL Query Latency (100GB dataset)
type: PropertyValue
value: Apache Hadoop: 15-45 seconds (Hive) | Google BigQuery: N/A

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

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

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

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

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

Query Performance (1TB dataset)
type: PropertyValue
value: Apache Hadoop: 120-300 seconds | Google BigQuery: 10-30 seconds
value reference: Google BigQuery

Annual TCO (100TB workload)
type: PropertyValue
value: Apache Hadoop: $150,000-$300,000 | Google BigQuery: $50,000-$75,000
value reference: Google BigQuery

Minimum Team Size
type: PropertyValue
value: Apache Hadoop: 4-8 (DevOps, engineers, admins) | Google BigQuery: 0-1 (analyst can self-serve)
value reference: Google BigQuery

Maximum Query Concurrency
type: PropertyValue
value: Apache Hadoop: 50-100 per cluster | Google BigQuery: Unlimited (auto-scaling)

Storage Cost (per TB/month)
type: PropertyValue
value: Apache Hadoop: $12-20 | Google BigQuery: $7 (BigQuery native)
value reference: Google BigQuery

Data Locality Advantage
type: PropertyValue
value: Apache Hadoop: 40-60% reduction in network I/O | Google BigQuery: 0% (cloud-native, N/A)
value reference: Apache Hadoop

Custom Algorithm Support (1-5 scale)
type: PropertyValue
value: Apache Hadoop: 5 (full MapReduce/Spark) | Google BigQuery: 2 (UDFs and built-in functions only)
value reference: Apache Hadoop

Query Performance on 1TB Dataset
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: 3-15 seconds

Cluster Setup Time
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: 0.25 hours

Cost per Core-Hour
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: $6.25 per TB scanned

Machine Learning Algorithms Available
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: 12-15 (BigQuery ML preset models)

Supported Languages/APIs
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: SQL, Python (BigQuery ML), JavaScript

Maximum Dataset Size Supported
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: Exabyte+

Cloud Provider Support
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: 1 (Google Cloud only)

Data Format Support
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: 5 formats (Parquet, ORC, Avro, CSV, JSON)

Query Latency (P95)
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: 1,000-10,000ms

Per-Query Cost (1TB scan)
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: $6.25

Data Ingestion Latency
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: 15-60 seconds (batch/streaming)

Setup Time to Production
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: 1 week

Maximum Cluster Size
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: Unlimited (serverless)

Events/Second Ingestion
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: 10,000/sec (batch)

Annual TCO (100TB dataset)
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: $625,000

P99 Query Latency
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: 100-500ms

Cloud Platform Support
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: Google Cloud only

TPC-DS 100TB Query Performance
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: 45 seconds

Query Latency (Median)
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: 5,000-30,000 ms

Streaming Ingestion Latency
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: 60-120 seconds

On-Demand Query Pricing
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: $6.25

Infrastructure Management
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: Fully serverless

Maximum Daily Event Throughput
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: Petabyte-scale (pricing limited)

Time to Deploy
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: 1-2 hours (sign-up to first query)

Concurrent Users Supported
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: 1000+ (automatic)

Median Query Latency
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: 1,000-10,000ms

Storage Cost
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: $0.02 (long-term storage)

Query Cost (On-Demand)
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: $6.25

SQL Standard Compliance
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: 100% ANSI SQL 2011

Deployment Options
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: Google Cloud only (serverless)

Operational Management Overhead
type: PropertyValue
value: Apache Hadoop: N/A | Google BigQuery: Minimal (fully managed, autoscaling)

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Apache Hadoop — Wikipedia
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Google BigQuery — Wikipedia
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Compare Apache Hadoop vs Google BigQuery
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Storage Cost (per TB/month)
type: PropertyValue
value reference: Cost

Data Locality Advantage
type: PropertyValue
value reference: Performance

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

Query Performance on 1TB Dataset
type: PropertyValue
value reference: Performance

Cluster Setup Time
type: PropertyValue
value reference: Implementation

Cost per Core-Hour
type: PropertyValue
value reference: Pricing

Machine Learning Algorithms Available
type: PropertyValue
value reference: ML Capabilities

Supported Languages/APIs
type: PropertyValue
value reference: Compatibility

Maximum Dataset Size Supported
type: PropertyValue
value reference: Performance

Cloud Provider Support
type: PropertyValue
value reference: Features

Data Format Support
type: PropertyValue
value reference: Flexibility

Query Latency (P95)
type: PropertyValue
value reference: Performance

Per-Query Cost (1TB scan)
type: PropertyValue
value reference: Pricing

Data Ingestion Latency
type: PropertyValue
value reference: Performance

Setup Time to Production
type: PropertyValue
value reference: Deployment

Maximum Cluster Size
type: PropertyValue
value reference: Scalability

Events/Second Ingestion
type: PropertyValue
value reference: Throughput

Annual TCO (100TB dataset)
type: PropertyValue
value reference: Total Cost

P99 Query Latency
type: PropertyValue
value reference: Performance

Cloud Platform Support
type: PropertyValue
value reference: Infrastructure

TPC-DS 100TB Query Performance
type: PropertyValue
value reference: Performance

Query Latency (Median)
type: PropertyValue
value reference: Performance

Streaming Ingestion Latency
type: PropertyValue
value reference: Real-time Capability

On-Demand Query Pricing
type: PropertyValue
value reference: Cost

Infrastructure Management
type: PropertyValue
value reference: Operations

Maximum Daily Event Throughput
type: PropertyValue
value reference: Scalability

Time to Deploy
type: PropertyValue
value reference: Time to Value

Concurrent Users Supported
type: PropertyValue
value reference: Scalability

Median Query Latency
type: PropertyValue
value reference: Performance

Storage Cost
type: PropertyValue
value reference: Pricing

Query Cost (On-Demand)
type: PropertyValue
value reference: Cost

SQL Standard Compliance
type: PropertyValue
value reference: Features

Deployment Options
type: PropertyValue
value reference: Infrastructure

Operational Management Overhead
type: PropertyValue
value reference: Operations