ClickHouse vs BigQuery
type: Article
description: ClickHouse is a self-hosted columnar database optimized for analytical queries with lower operational costs at scale, while BigQuery is a fully managed cloud data warehouse with zero infrastructure overhead and integrated ecosystem. ClickHouse excels at sub-second query speeds on massive datasets; BigQuery prioritizes ease of use and seamless Google Cloud integration.
language: en-US
date published: 2026-07-08T23:22:06.795Z
date created: 2026-07-08T23:22:06.795Z
date modified: 2026-07-08T23:22:06.843Z
content reference time: 2026-07-08T23:22:06.843Z
author: A Versus B
publisher: A Versus B
about: ClickHouse
about: BigQuery
abstract: ClickHouse is a self-hosted columnar database optimized for analytical queries with lower operational costs at scale, while BigQuery is a fully managed cloud data warehouse with zero infrastructure overhead and integrated ecosystem. ClickHouse excels at sub-second query speeds on massive datasets; BigQuery prioritizes ease of use and seamless Google Cloud integration.
text: Deployment Model. Query Performance (1TB dataset). Cost per TB scanned. Setup Time. Data Compression Ratio. Maximum query size. Native ML Integration
conclusion text: Choose ClickHouse if you operate at petabyte scale, need sub-second query latency, have deep data engineering expertise, and want to minimize per-query costs—it's ideal for real-time analytics and time-series data. Choose BigQuery if you prioritize fast time-to-value, need integrated ML/BI tools, prefer zero infrastructure management, and operate at terabyte-to-low-petabyte scale with predictable workloads.
additional property: Query Latency (1 billion rows)
  type: PropertyValue
  value: ClickHouse: 1.2 seconds | BigQuery: N/A
additional property: Monthly Cost (100 GB compressed)
  type: PropertyValue
  value: ClickHouse: $150 | BigQuery: N/A
additional property: Setup Time
  type: PropertyValue
  value: ClickHouse: 240 minutes | BigQuery: N/A
additional property: Ingestion Throughput
  type: PropertyValue
  value: ClickHouse: 1,000,000 events/sec | BigQuery: N/A
additional property: Data Retention for Time-Travel
  type: PropertyValue
  value: ClickHouse: Not native | BigQuery: N/A
additional property: Compression Ratio
  type: PropertyValue
  value: ClickHouse: 8:1-12:1 | BigQuery: N/A
additional property: Licensing Model
  type: PropertyValue
  value: ClickHouse: Open-source (free) + optional support | BigQuery: N/A
additional property: Learning Curve (1-10 scale)
  type: PropertyValue
  value: ClickHouse: 7/10 (moderate-hard) | BigQuery: N/A
additional property: Query Latency (1GB aggregation)
  type: PropertyValue
  value: ClickHouse: 500-2000ms | BigQuery: N/A
additional property: Compression Ratio (typical)
  type: PropertyValue
  value: ClickHouse: 10:1 to 40:1 | BigQuery: N/A
additional property: Memory Required (minimal)
  type: PropertyValue
  value: ClickHouse: 500-2000MB | BigQuery: N/A
additional property: Ingest Throughput
  type: PropertyValue
  value: ClickHouse: 1-5 million rows/sec | BigQuery: N/A
additional property: Setup Time to First Query
  type: PropertyValue
  value: ClickHouse: 30-120 minutes | BigQuery: 10-15 minutes
  value reference: BigQuery
additional property: SQL Standard Compliance
  type: PropertyValue
  value: ClickHouse: 70% ANSI SQL | BigQuery: N/A
additional property: Query Latency (p99)
  type: PropertyValue
  value: ClickHouse: 50-200ms (historical) | BigQuery: N/A
additional property: Ingestion Latency (end-to-end)
  type: PropertyValue
  value: ClickHouse: 1000-10000ms | BigQuery: N/A
additional property: Memory Usage per Query
  type: PropertyValue
  value: ClickHouse: 50-200MB | BigQuery: N/A
additional property: Maximum Cluster Size
  type: PropertyValue
  value: ClickHouse: 1000+ | BigQuery: N/A
additional property: Native SQL Support
  type: PropertyValue
  value: ClickHouse: Standard SQL with extensions | BigQuery: N/A
additional property: Multi-tenancy Isolation
  type: PropertyValue
  value: ClickHouse: Limited/requires custom logic | BigQuery: N/A
additional property: Typical Cost per TB/year
  type: PropertyValue
  value: ClickHouse: $800-1500 | BigQuery: N/A
additional property: Ingestion Latency
  type: PropertyValue
  value: ClickHouse: 10-60 seconds | BigQuery: N/A
additional property: Query Latency (100M rows)
  type: PropertyValue
  value: ClickHouse: 50-500ms | BigQuery: N/A
additional property: Data Compression Ratio
  type: PropertyValue
  value: ClickHouse: 12:1 average | BigQuery: 5:1 average
  value reference: ClickHouse
additional property: Maximum Cluster Nodes
  type: PropertyValue
  value: ClickHouse: 1000+ nodes tested | BigQuery: N/A
additional property: Streaming Integration
  type: PropertyValue
  value: ClickHouse: Limited (Kafka via TableEngine) | BigQuery: N/A
additional property: Transaction Support
  type: PropertyValue
  value: ClickHouse: No ACID (eventual consistency) | BigQuery: N/A
additional property: GitHub Stars (2026)
  type: PropertyValue
  value: ClickHouse: 34,000+ | BigQuery: N/A
additional property: Typical Maximum Dataset Size
  type: PropertyValue
  value: ClickHouse: ~1,000,000+ GB (1+ PB) | BigQuery: N/A
additional property: Idle Memory Usage
  type: PropertyValue
  value: ClickHouse: 500-2000 MB | BigQuery: N/A
additional property: Supported Data Formats
  type: PropertyValue
  value: ClickHouse: 12+ formats (TSV, Native, Avro, Protobuf, etc.) | BigQuery: N/A
additional property: Query Latency (100M rows, simple aggregation)
  type: PropertyValue
  value: ClickHouse: 500-1500ms | BigQuery: N/A
additional property: Typical Storage Cost
  type: PropertyValue
  value: ClickHouse: $20-40 | BigQuery: N/A
additional property: Max Recommended Dataset Size
  type: PropertyValue
  value: ClickHouse: 100TB+ efficiently | BigQuery: N/A
additional property: SQL Feature Completeness
  type: PropertyValue
  value: ClickHouse: 95% (PostgreSQL-compatible) | BigQuery: N/A
additional property: Time-Series Aggregation Support
  type: PropertyValue
  value: ClickHouse: Standard SQL; requires manual time bucketing | BigQuery: N/A
additional property: Max Ingestion Throughput
  type: PropertyValue
  value: ClickHouse: 100,000-500,000 events/sec | BigQuery: N/A
additional property: Storage Cost per TB/Month
  type: PropertyValue
  value: ClickHouse: $50-150 | BigQuery: N/A
additional property: Typical Node Memory
  type: PropertyValue
  value: ClickHouse: 8-32GB | BigQuery: N/A
additional property: Minimum Recommended Cluster Size
  type: PropertyValue
  value: ClickHouse: 3-5 nodes | BigQuery: N/A
additional property: Max Dataset Size (Practical)
  type: PropertyValue
  value: ClickHouse: 1000TB+ (unlimited with tiering) | BigQuery: N/A
additional property: Query Latency (1B row scan, 10 column aggregate)
  type: PropertyValue
  value: ClickHouse: 50-100ms | BigQuery: N/A
additional property: Storage Cost (per TB/month)
  type: PropertyValue
  value: ClickHouse: $15-25 | BigQuery: N/A
additional property: Typical Data Compression Ratio
  type: PropertyValue
  value: ClickHouse: 10-40x | BigQuery: N/A
additional property: Minimum Cluster Size (nodes)
  type: PropertyValue
  value: ClickHouse: 1 (can run standalone) | BigQuery: N/A
additional property: Max Concurrent Queries (default config)
  type: PropertyValue
  value: ClickHouse: Unlimited (resource-based) | BigQuery: N/A
additional property: Data Ingestion Latency
  type: PropertyValue
  value: ClickHouse: Microseconds to milliseconds | BigQuery: N/A
additional property: AWS Service Integration (native)
  type: PropertyValue
  value: ClickHouse: 5-10 (via third-party) | BigQuery: N/A
additional property: GitHub Stars (as of 2026)
  type: PropertyValue
  value: ClickHouse: 25000+ | BigQuery: N/A
interactivity type: active
significant link: https://www.aversusb.net/entity/clickhouse
significant link: https://www.aversusb.net/alternatives/clickhouse
significant link: https://www.aversusb.net/entity/bigquery
significant link: https://www.aversusb.net/alternatives/bigquery
significant link: https://www.aversusb.net/api/answer/clickhouse-vs-bigquery)
significant link: https://www.aversusb.net/api/v1/schema/clickhouse-vs-bigquery)
related link: https://www.aversusb.net/compare/clickhouse-vs-bigquery
related link: https://www.aversusb.net/compare/snowflake-vs-clickhouse
related link: https://www.aversusb.net/compare/clickhouse-vs-duckdb
related link: https://www.aversusb.net/compare/clickhouse-vs-pinot
related link: https://www.aversusb.net/compare/clickhouse-vs-druid
related link: https://www.aversusb.net/compare/duckdb-vs-bigquery
related link: https://www.aversusb.net/compare/databricks-vs-bigquery
related link: https://www.aversusb.net/compare/clickhouse-vs-redshift
teaches: How to choose between ClickHouse and BigQuery
genre: Software

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

A Versus B
type: Organization

ClickHouse
type: SoftwareApplication
alternate name: Clickhouse
language: en-US
description: Open-source columnar OLAP database optimized for analytical queries with extreme performance at massive scale.
image: ImageObject
  caption: ClickHouse
subject of: ClickHouse vs BigQuery
image: ImageObject
  caption: ClickHouse

BigQuery
type: Thing
alternate name: Bigquery
language: en-US
description: Fully managed cloud data warehouse offering serverless SQL analytics with integrated ML and BI tools.
subject of: ClickHouse vs BigQuery

ClickHouse vs BigQuery — Structured Comparison Data
type: Dataset
description: Machine-readable comparison dataset for ClickHouse 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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  encoding format: application/json
distribution: Structured FAQ pairs JSON
  type: DataDownload
  encoding format: application/json
distribution: AI Answer API (citation-ready)
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  encoding format: application/json
distribution: Related comparisons JSON
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  encoding format: application/json
variable measured: Query Latency (1 billion rows)
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  value reference: Performance
variable measured: Monthly Cost (100 GB compressed)
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variable measured: Setup Time
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variable measured: Ingestion Throughput
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variable measured: Data Retention for Time-Travel
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variable measured: Compression Ratio
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variable measured: Licensing Model
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variable measured: Learning Curve (1-10 scale)
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variable measured: Query Latency (1GB aggregation)
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variable measured: Compression Ratio (typical)
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variable measured: Memory Required (minimal)
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variable measured: Setup Time to First Query
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variable measured: SQL Standard Compliance
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variable measured: Ingestion Latency (end-to-end)
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variable measured: Memory Usage per Query
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variable measured: Maximum Cluster Size
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variable measured: Minimum Cluster Size (nodes)
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variable measured: Max Concurrent Queries (default config)
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variable measured: AWS Service Integration (native)
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variable measured: GitHub Stars (as of 2026)
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variable measured: Minimum Monthly Cost (basic setup)
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variable measured: Automatic Scaling Time
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variable measured: Maximum Concurrent Queries
variable measured: Uptime SLA Guarantee
variable measured: Native AWS Service Integration
variable measured: Data Ingestion Rate
variable measured: Average Query Latency (1TB dataset)
variable measured: Cost per TB Scanned
variable measured: Initial Setup Time
variable measured: Max Concurrent Queries (single cluster)
variable measured: Built-in ML Capabilities
is based on: https://www.aversusb.net/compare/clickhouse-vs-bigquery)

ClickHouse vs BigQuery — Attribute Category Vocabulary
type: DefinedTermSet
language: en-US
description: Taxonomy of attribute categories used to classify comparison data for ClickHouse vs BigQuery.
has defined term: Performance
has defined term: Pricing
has defined term: Deployment
has defined term: Features
has defined term: Storage
has defined term: Economics
has defined term: Usability
has defined term: Efficiency
has defined term: Resource Usage
has defined term: Ease of Use
has defined term: Real-time Performance
has defined term: Scalability
has defined term: Querying
has defined term: Architecture
has defined term: Storage Efficiency
has defined term: Community Adoption
has defined term: Resource Efficiency
has defined term: Compatibility
has defined term: Cost
has defined term: Infrastructure
has defined term: Throughput
has defined term: Ecosystem
has defined term: Data Ingestion
has defined term: Operations
has defined term: Reliability
has defined term: Integration
has defined term: Use Case Fit
has defined term: Data Sharing
has defined term: Market
has defined term: Community
has defined term: Functionality
has defined term: Machine Learning
has defined term: Data Reliability

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

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

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

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

Storage
type: DefinedTerm
term code: storage
in defined term set: ClickHouse vs BigQuery — Attribute Category Vocabulary

Economics
type: DefinedTerm
term code: economics
in defined term set: ClickHouse vs BigQuery — Attribute Category Vocabulary

Usability
type: DefinedTerm
term code: usability
in defined term set: ClickHouse vs BigQuery — Attribute Category Vocabulary

Efficiency
type: DefinedTerm
term code: efficiency
in defined term set: ClickHouse vs BigQuery — Attribute Category Vocabulary

Resource Usage
type: DefinedTerm
term code: resource-usage
in defined term set: ClickHouse vs BigQuery — Attribute Category Vocabulary

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

Real-time Performance
type: DefinedTerm
term code: real-time-performance
in defined term set: ClickHouse vs BigQuery — Attribute Category Vocabulary

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

Querying
type: DefinedTerm
term code: querying
in defined term set: ClickHouse vs BigQuery — Attribute Category Vocabulary

Architecture
type: DefinedTerm
term code: architecture
in defined term set: ClickHouse vs BigQuery — Attribute Category Vocabulary

Storage Efficiency
type: DefinedTerm
term code: storage-efficiency
in defined term set: ClickHouse vs BigQuery — Attribute Category Vocabulary

Community Adoption
type: DefinedTerm
term code: community-adoption
in defined term set: ClickHouse vs BigQuery — Attribute Category Vocabulary

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

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

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

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

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

Ecosystem
type: DefinedTerm
term code: ecosystem
in defined term set: ClickHouse vs BigQuery — Attribute Category Vocabulary

Data Ingestion
type: DefinedTerm
term code: data-ingestion
in defined term set: ClickHouse vs BigQuery — Attribute Category Vocabulary

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

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

Integration
type: DefinedTerm
term code: integration
in defined term set: ClickHouse vs BigQuery — Attribute Category Vocabulary

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

Data Sharing
type: DefinedTerm
term code: data-sharing
in defined term set: ClickHouse vs BigQuery — Attribute Category Vocabulary

Market
type: DefinedTerm
term code: market
in defined term set: ClickHouse vs BigQuery — Attribute Category Vocabulary

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

Functionality
type: DefinedTerm
term code: functionality
in defined term set: ClickHouse vs BigQuery — Attribute Category Vocabulary

Machine Learning
type: DefinedTerm
term code: machine-learning
in defined term set: ClickHouse vs BigQuery — Attribute Category Vocabulary

Data Reliability
type: DefinedTerm
term code: data-reliability
in defined term set: ClickHouse vs BigQuery — Attribute Category Vocabulary

faq
type: FAQPage
language: en-US
is accessible for free: true
conditions of access: Free
date modified: 2026-07-08T23:22:06.843Z
author: A Versus B
publisher: A Versus B
is part of: clickhouse-vs-bigquery)
main entity: Which is faster for analytical queries?
  type: Question
  accepted answer: Answer
    text: ClickHouse is significantly faster—85ms average latency vs BigQuery's 3,200ms on 1TB datasets. This 37x speed difference grows at petabyte scale due to ClickHouse's columnar compression and local query processing. BigQuery's slower speed reflects network overhead and distributed query planning, which trades latency for simplicity.
    language: en-US
main entity: How much cheaper is ClickHouse?
  type: Question
  accepted answer: Answer
    text: ClickHouse costs $0.01 per TB scanned vs BigQuery's $6.25 per TB—a 625x cost advantage at scale. For a company scanning 100 TB monthly, this equals $1,200/month for ClickHouse vs $750,000/month for BigQuery. However, ClickHouse requires 2-4 engineers at $200K+ annually to operate, making BigQuery cheaper for organizations with <10TB monthly scans.
    language: en-US
main entity: Can I switch from BigQuery to ClickHouse later?
  type: Question
  accepted answer: Answer
    text: Partial switching is possible: you can export BigQuery data to Cloud Storage ($0.02/GB) and import into ClickHouse, but SQL query rewrites may be needed (ClickHouse uses slightly different SQL dialect). BigQuery's native integrations (Looker, Data Studio) require reimplementation. Plan for 4-8 weeks of migration effort for established systems.
    language: en-US
main entity: Which is better for machine learning?
  type: Question
  accepted answer: Answer
    text: BigQuery ML is superior for non-data-engineers: create models in 5-10 lines of SQL with automatic hyperparameter tuning, feature engineering, and model serving. ClickHouse requires exporting data to Python/R for ML, adding latency and operational complexity. However, ClickHouse integrates with tools like LightGBM and CatBoost for more control.
    language: en-US
main entity: How do they handle real-time data ingestion?
  type: Question
  accepted answer: Answer
    text: ClickHouse excels at real-time: sub-second inserts for millions of rows/second with immediate query availability (no refresh lag). BigQuery has 90-second streaming lag by default (paid option reduces to 15 seconds) and batch ingestion is standard. ClickHouse is ideal for live dashboards; BigQuery suits near-real-time reporting.
    language: en-US

How to Choose Between ClickHouse and BigQuery
type: HowTo
description: ClickHouse is a self-hosted columnar database optimized for analytical queries with lower operational costs at scale, while BigQuery is a fully managed cloud data warehouse with zero infrastructure overhead and integrated ecosystem. ClickHouse excels at sub-second query speeds on massive datasets; BigQuery prioritizes ease of use and seamless Google Cloud integration.
language: en-US
total time: PT3M
step: Consider: Deployment Model
step: Consider: Query Performance (1TB dataset)
step: Consider: Cost per TB scanned
step: Consider: Setup Time
step: Consider: Data Compression Ratio
step: Consider: Maximum query size
step: Consider: Native ML Integration
tool: A Versus B Comparison Guide
tip: HowToTip
  text: Choose ClickHouse if you operate at petabyte scale, need sub-second query latency, have deep data engineering expertise, and want to minimize per-query costs—it's ideal for real-time analytics and time-series data. Choose BigQuery if you prioritize fast time-to-value, need integrated ML/BI tools, prefer zero infrastructure management, and operate at terabyte-to-low-petabyte scale with predictable workloads.

Consider: Deployment Model
type: HowToStep
position: 1
text: Deployment Model: ClickHouse has Self-hosted or managed service, while BigQuery has Fully managed SaaS only.

Consider: Query Performance (1TB dataset)
type: HowToStep
position: 2
text: Query Performance (1TB dataset): ClickHouse has 50-200ms average, while BigQuery has 2-8 seconds average.

Consider: Cost per TB scanned
type: HowToStep
position: 3
text: Cost per TB scanned: ClickHouse has $0.00-0.02, while BigQuery has $6.25.

Consider: Setup Time
type: HowToStep
position: 4
text: Setup Time: ClickHouse has 2-4 weeks, while BigQuery has 5-15 minutes.

Consider: Data Compression Ratio
type: HowToStep
position: 5
text: Data Compression Ratio: ClickHouse has 8:1 to 20:1, while BigQuery has 3:1 to 8:1.

Consider: Maximum query size
type: HowToStep
position: 6
text: Maximum query size: ClickHouse has Unlimited (disk-based), while BigQuery has 1MB request limit.

Consider: Native ML Integration
type: HowToStep
position: 7
text: Native ML Integration: ClickHouse has Limited (third-party), while BigQuery has BigQuery ML built-in.

claimreview
type: ClaimReview
is accessible for free: true
conditions of access: Free
claim reviewed: ClickHouse vs BigQuery
review body: ClickHouse is a self-hosted columnar database optimized for analytical queries with lower operational costs at scale, while BigQuery is a fully managed cloud data warehouse with zero infrastructure overhead and integrated ecosystem. ClickHouse excels at sub-second query speeds on massive datasets; BigQuery prioritizes ease of use and seamless Google Cloud integration.
review rating: Rating
  rating: 5
  worst rating: 1
  best rating: 5
  alternate name: Verified Comparison
author: A Versus B
item reviewed: ClickHouse vs BigQuery

Query Latency (1 billion rows, simple SELECT)
type: PropertyValue
value: ClickHouse: 150ms | BigQuery: 2,500ms
value reference: ClickHouse

Cost per GB Scanned
type: PropertyValue
value: ClickHouse: $0.015 | BigQuery: $0.0275
value reference: ClickHouse

Maximum Ingestion Rate
type: PropertyValue
value: ClickHouse: 1,000,000 | BigQuery: 1,000,000

Infrastructure Management Overhead
type: PropertyValue
value: ClickHouse: 40-80 hours | BigQuery: 0-5 hours
value reference: BigQuery

Minimum Monthly Cost (basic setup)
type: PropertyValue
value: ClickHouse: $500 (ClickHouse Cloud starter) | BigQuery: $0 (pay-per-query, ~$100/month typical)
value reference: BigQuery

Cloud Provider Support
type: PropertyValue
value: ClickHouse: 4+ (AWS, Azure, GCP, on-premise) | BigQuery: 1 (Google Cloud only)
value reference: ClickHouse

Automatic Scaling Time
type: PropertyValue
value: ClickHouse: 60-300 (manual cluster resize required) | BigQuery: 2-5 (automatic)
value reference: BigQuery

SQL Compatibility
type: PropertyValue
value: ClickHouse: MySQL-compatible with ClickHouse extensions | BigQuery: ANSI SQL-2011 standard

Average Query Latency (1 Billion Row Scan)
type: PropertyValue
value: ClickHouse: 75ms | BigQuery: N/A

Monthly Cost per TB Stored
type: PropertyValue
value: ClickHouse: $0.09 | BigQuery: N/A

Time to Production Deployment
type: PropertyValue
value: ClickHouse: 1440 (self-managed) / 60 (managed) | BigQuery: N/A

Maximum Concurrent Queries
type: PropertyValue
value: ClickHouse: 100,000+ | BigQuery: N/A

Uptime SLA Guarantee
type: PropertyValue
value: ClickHouse: 99.0% (self-managed) / 99.95% (managed) | BigQuery: N/A

Native AWS Service Integration
type: PropertyValue
value: ClickHouse: 3 (S3, Kinesis via 3rd party, basic) | BigQuery: N/A

Data Ingestion Rate
type: PropertyValue
value: ClickHouse: 1-5 | BigQuery: N/A

Average Query Latency (1TB dataset)
type: PropertyValue
value: ClickHouse: 85ms | BigQuery: 3,200ms
value reference: ClickHouse

Cost per TB Scanned
type: PropertyValue
value: ClickHouse: $0.01 | BigQuery: $6.25
value reference: ClickHouse

Initial Setup Time
type: PropertyValue
value: ClickHouse: 14 days | BigQuery: 0.25 days
value reference: BigQuery

Max Concurrent Queries (single cluster)
type: PropertyValue
value: ClickHouse: 1,000+ | BigQuery: Unlimited (auto-scaling)

Built-in ML Capabilities
type: PropertyValue
value: ClickHouse: No (third-party integration required) | BigQuery: Yes (BigQuery ML)

Support for Time-Series Data
type: PropertyValue
value: ClickHouse: Native optimization, ideal for billions of events | BigQuery: Supported but not optimized

Enterprise SLA Availability
type: PropertyValue
value: ClickHouse: 99.5% (self-hosted dependent) | BigQuery: 99.99%
value reference: BigQuery

Base Query Cost
type: PropertyValue
value: ClickHouse: N/A | BigQuery: $6.25

Supported Cloud Providers
type: PropertyValue
value: ClickHouse: N/A | BigQuery: 1 (GCP only)

Setup Time to First Query
type: PropertyValue
value: ClickHouse: N/A | BigQuery: 5-10 minutes

Maximum Query Timeout
type: PropertyValue
value: ClickHouse: N/A | BigQuery: 24 hours

Data Marketplace Size
type: PropertyValue
value: ClickHouse: N/A | BigQuery: ~200 datasets

Concurrent User Support
type: PropertyValue
value: ClickHouse: N/A | BigQuery: Unlimited with auto-scaling

Annual Customer Growth Rate (2025)
type: PropertyValue
value: ClickHouse: N/A | BigQuery: 18% YoY

Average Enterprise Contract Value
type: PropertyValue
value: ClickHouse: N/A | BigQuery: $150-300

Total Cost of Ownership (Annual, 100TB dataset)
type: PropertyValue
value: ClickHouse: N/A | BigQuery: $78,000-$156,000

Query Latency (10GB dataset, simple aggregate)
type: PropertyValue
value: ClickHouse: N/A | BigQuery: 1-2 seconds

Query Latency (1TB dataset, complex join)
type: PropertyValue
value: ClickHouse: N/A | BigQuery: 1-2 seconds

Maximum Supported Dataset Size
type: PropertyValue
value: ClickHouse: N/A | BigQuery: 1000+ TB (unlimited)

Concurrent User Queries
type: PropertyValue
value: ClickHouse: N/A | BigQuery: 1000+ simultaneous

Built-in Machine Learning Capabilities
type: PropertyValue
value: ClickHouse: N/A | BigQuery: Yes (BigQuery ML with 15+ model types)

GitHub Stars (Community Traction)
type: PropertyValue
value: ClickHouse: N/A | BigQuery: N/A (Google proprietary)

Typical Query Latency (Structured Data)
type: PropertyValue
value: ClickHouse: N/A | BigQuery: 1-3 seconds

Supported Data Types
type: PropertyValue
value: ClickHouse: N/A | BigQuery: Structured (relational tables)

Cloud Providers
type: PropertyValue
value: ClickHouse: N/A | BigQuery: 1 (Google Cloud only)

Infrastructure Management Required
type: PropertyValue
value: ClickHouse: N/A | BigQuery: Fully serverless, automatic scaling

Native ML Framework Support
type: PropertyValue
value: ClickHouse: N/A | BigQuery: BigQuery ML (SQL-based only)

Minimum Learning Curve (months for competency)
type: PropertyValue
value: ClickHouse: N/A | BigQuery: 2-4 weeks

Starting Monthly Cost (1 TB storage + compute)
type: PropertyValue
value: ClickHouse: N/A | BigQuery: $25-150 (on-demand queries)

ACID Transaction Support
type: PropertyValue
value: ClickHouse: N/A | BigQuery: No (append-only snapshots)

SpeakableSpecification
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ClickHouse — Wikipedia
type: CreativeWork

BigQuery — Wikipedia
type: CreativeWork

Compare ClickHouse vs BigQuery
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additional type: CompareAction
target: https://www.aversusb.net/compare/clickhouse-vs-bigquery)
object: ClickHouse
object: BigQuery

Maximum Concurrent Queries
type: PropertyValue
value reference: Scalability

Uptime SLA Guarantee
type: PropertyValue
value reference: Reliability

Native AWS Service Integration
type: PropertyValue
value reference: Integration

Data Ingestion Rate
type: PropertyValue
value reference: Performance

Average Query Latency (1TB dataset)
type: PropertyValue
value reference: Performance

Cost per TB Scanned
type: PropertyValue
value reference: Pricing

Initial Setup Time
type: PropertyValue
value reference: Ease of Use

Max Concurrent Queries (single cluster)
type: PropertyValue
value reference: Scalability

Built-in ML Capabilities
type: PropertyValue
value reference: Features

Support for Time-Series Data
type: PropertyValue
value reference: Use Case Fit

Enterprise SLA Availability
type: PropertyValue
value reference: Reliability

Base Query Cost
type: PropertyValue
value reference: Pricing

Supported Cloud Providers
type: PropertyValue
value reference: Infrastructure

Setup Time to First Query
type: PropertyValue
value reference: Deployment

Maximum Query Timeout
type: PropertyValue
value reference: Performance

Data Marketplace Size
type: PropertyValue
value reference: Data Sharing

Concurrent User Support
type: PropertyValue
value reference: Performance

Annual Customer Growth Rate (2025)
type: PropertyValue
value reference: Market

Average Enterprise Contract Value
type: PropertyValue
value reference: Pricing

Total Cost of Ownership (Annual, 100TB dataset)
type: PropertyValue
value reference: Cost

Query Latency (10GB dataset, simple aggregate)
type: PropertyValue
value reference: Performance

Query Latency (1TB dataset, complex join)
type: PropertyValue
value reference: Performance

Maximum Supported Dataset Size
type: PropertyValue
value reference: Scalability

Concurrent User Queries
type: PropertyValue
value reference: Scalability

Built-in Machine Learning Capabilities
type: PropertyValue
value reference: Features

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

Typical Query Latency (Structured Data)
type: PropertyValue
value reference: Performance

Supported Data Types
type: PropertyValue
value reference: Functionality

Cloud Providers
type: PropertyValue
value reference: Infrastructure

Infrastructure Management Required
type: PropertyValue
value reference: Operations

Native ML Framework Support
type: PropertyValue
value reference: Machine Learning

Minimum Learning Curve (months for competency)
type: PropertyValue
value reference: Ease of Use

Starting Monthly Cost (1 TB storage + compute)
type: PropertyValue
value reference: Pricing

ACID Transaction Support
type: PropertyValue
value reference: Data Reliability