DuckDB vs ClickHouse
type: WebPage
description: DuckDB is an in-process OLAP database optimized for analytical queries on local datasets with minimal setup, while ClickHouse is a distributed columnar database designed for large-scale, high-throughput analytics across multiple servers. DuckDB excels in simplicity and embedded use cases; ClickHouse dominates in handling massive data volumes and complex distributed queries.
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date published: 2026-07-09T15:31:23.133Z
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caption: DuckDB vs ClickHouse — Side-by-side comparison on A Versus B

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DuckDB vs ClickHouse
type: Article
type: TechArticle
abstract: DuckDB is an in-process OLAP database optimized for analytical queries on local datasets with minimal setup, while ClickHouse is a distributed columnar database designed for large-scale, high-throughput analytics across multiple servers. DuckDB excels in simplicity and embedded use cases; ClickHouse dominates in handling massive data volumes and complex distributed queries.
description: DuckDB is an in-process OLAP database optimized for analytical queries on local datasets with minimal setup, while ClickHouse is a distributed columnar database designed for large-scale, high-throughput analytics across multiple servers. DuckDB excels in simplicity and embedded use cases; ClickHouse dominates in handling massive data volumes and complex distributed queries.
language: en-US
main entity of page: DuckDB vs ClickHouse
content reference time: 2026-07-09T15:31:23.186Z
author: A Versus B
publisher: A Versus B
date published: 2026-07-09T15:31:23.133Z
date created: 2026-07-09T15:31:23.133Z
date modified: 2026-07-09T15:31:23.186Z
text: Choose DuckDB if you need a lightweight, easy-to-deploy analytical database for datasets under 1TB, embedded analytics in applications, or rapid prototyping without infrastructure overhead. Choose ClickHouse if you're processing petabyte-scale data, require distributed query execution across dozens of nodes, need sub-second response times on massive aggregations, and have the operational expertise to manage a cluster.
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  object: ClickHouse
about: DuckDB
about: ClickHouse
mentions: Deployment Model
mentions: Setup Complexity
mentions: Query Performance at 10GB
mentions: Maximum Practical Dataset Size
mentions: SQL Dialect Compatibility
mentions: License
mentions: Operational Overhead
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citation: DuckDB — Wikipedia
citation: ClickHouse — Wikipedia
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significant link: https://www.aversusb.net/entity/clickhouse
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A Versus B
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DuckDB
type: SoftwareApplication
description: Embedded analytical SQL database optimized for in-process OLAP queries
alternate name: Duckdb
language: en-US
image: ImageObject
  caption: DuckDB
subject of: DuckDB vs ClickHouse

ClickHouse
type: SoftwareApplication
description: Distributed column-oriented OLAP database for petabyte-scale analytics
alternate name: Clickhouse
language: en-US
image: ImageObject
  caption: ClickHouse
subject of: DuckDB vs ClickHouse

DuckDB vs ClickHouse — Comparison Data
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description: Structured comparison data for DuckDB vs ClickHouse with 180 attributes.
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license: https://creativecommons.org/licenses/by/4.0/
creator: A Versus B
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variable measured: Maximum Cluster Size
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DuckDB vs ClickHouse — Attribute Category Vocabulary
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language: en-US
description: Taxonomy of attribute categories used to classify comparison data for DuckDB vs ClickHouse.
has defined term: Scalability
has defined term: Performance
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has defined term: Throughput
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has defined term: Maturity
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has defined term: Ease of Use
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has defined term: SQL Features
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has defined term: Quotas
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has defined term: Setup
has defined term: Operational
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has defined term: Adoption & Community
has defined term: Learning
has defined term: Query Language
has defined term: Usability
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has defined term: Licensing
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has defined term: Economics
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has defined term: Data Ingestion
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has defined term: User Experience
has defined term: Use Case Fit
has defined term: SQL Support
has defined term: Operational Complexity
has defined term: Setup Speed
has defined term: Resource Requirements
has defined term: Streaming

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term code: scalability
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

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

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

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

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

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

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

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

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

Concurrency
type: DefinedTerm
term code: concurrency
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Maturity
type: DefinedTerm
term code: maturity
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

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

Adoption
type: DefinedTerm
term code: adoption
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

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

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

Feature Completeness
type: DefinedTerm
term code: feature-completeness
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Data Integrity
type: DefinedTerm
term code: data-integrity
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Implementation
type: DefinedTerm
term code: implementation
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Ecosystem
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term code: ecosystem
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Development
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term code: development
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Cost
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term code: cost
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Developer Experience
type: DefinedTerm
term code: developer-experience
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

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

API Completeness
type: DefinedTerm
term code: api-completeness
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Community Support
type: DefinedTerm
term code: community-support
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

SQL Features
type: DefinedTerm
term code: sql-features
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Workflow Speed
type: DefinedTerm
term code: workflow-speed
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

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

Quotas
type: DefinedTerm
term code: quotas
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Localization
type: DefinedTerm
term code: localization
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Setup
type: DefinedTerm
term code: setup
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Operational
type: DefinedTerm
term code: operational
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Resources
type: DefinedTerm
term code: resources
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

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

Learning
type: DefinedTerm
term code: learning
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Query Language
type: DefinedTerm
term code: query-language
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

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

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

Licensing
type: DefinedTerm
term code: licensing
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Resource Footprint
type: DefinedTerm
term code: resource-footprint
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Clustering
type: DefinedTerm
term code: clustering
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

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

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

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

Support & Licensing
type: DefinedTerm
term code: support-&-licensing
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

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

Legal & Cost
type: DefinedTerm
term code: legal-&-cost
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

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

Querying
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term code: querying
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Economics
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term code: economics
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

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

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

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

Operability
type: DefinedTerm
term code: operability
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

User Experience
type: DefinedTerm
term code: user-experience
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

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

SQL Support
type: DefinedTerm
term code: sql-support
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Operational Complexity
type: DefinedTerm
term code: operational-complexity
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Setup Speed
type: DefinedTerm
term code: setup-speed
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Resource Requirements
type: DefinedTerm
term code: resource-requirements
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

Streaming
type: DefinedTerm
term code: streaming
in defined term set: DuckDB vs ClickHouse — Attribute Category Vocabulary

faq
type: FAQPage
language: en-US
is accessible for free: true
conditions of access: Free
date modified: 2026-07-09T15:31:23.186Z
author: A Versus B
publisher: A Versus B
is part of: DuckDB vs ClickHouse
main entity: When should I choose DuckDB over ClickHouse?
  type: Question
  accepted answer: Answer
    text: Choose DuckDB if your dataset is under 1TB, you need zero operational overhead, you want a database that embeds directly in your application with no separate server infrastructure, or you're building data analysis tools for Python/R/JavaScript environments. DuckDB is ideal for data scientists, analysts working with local datasets, and teams prioritizing simplicity over distributed scale.
    language: en-US
main entity: Can DuckDB handle real-time data ingestion like ClickHouse?
  type: Question
  accepted answer: Answer
    text: DuckDB supports data ingestion but is optimized for analytical queries on static or batch-loaded datasets. ClickHouse excels at real-time event streaming with insert rates of 1M+ rows per second, native Kafka integration, and built-in data replication. For real-time analytics at scale (>100K events/second), ClickHouse is the better choice.
    language: en-US
main entity: What are the licensing implications of using ClickHouse commercially?
  type: Question
  accepted answer: Answer
    text: ClickHouse is licensed under AGPL v3, which requires that any modifications or derivative works using ClickHouse must publish their source code. Organizations can: (1) use ClickHouse unmodified under AGPL, (2) purchase a commercial license from ClickHouse Inc. to use proprietary modifications, or (3) use DuckDB's MIT license if source code privacy is critical. Many enterprises choose the commercial license to avoid AGPL obligations.
    language: en-US
main entity: How do query languages differ between DuckDB and ClickHouse?
  type: Question
  accepted answer: Answer
    text: DuckDB uses standard SQL with PostgreSQL extensions, making it nearly 100% compatible with PostgreSQL syntax and allowing easy migration. ClickHouse uses ClickHouse SQL, a custom dialect with extensions like specialized aggregation functions (quantiles, groupArrayInsertAt) and lacks some standard features (common table expressions with limited support). Teams familiar with PostgreSQL will find DuckDB's SQL more intuitive, while ClickHouse's SQL is more powerful for specific analytics use cases.
    language: en-US
main entity: Which database is better for machine learning preprocessing?
  type: Question
  accepted answer: Answer
    text: DuckDB integrates seamlessly with Python/R/Arrow ecosystems, making it superior for ML preprocessing pipelines. It has native support for DuckDB-Arrow format, Parquet files, and Python UDFs. ClickHouse requires additional ETL steps to export data for ML. For ML workflows, DuckDB is the clear choice due to its tight integration with data science tools and zero operational friction.
    language: en-US

Base Monthly Cost
type: PropertyValue
value reference: Pricing

Free Tier Storage
type: PropertyValue
value reference: Pricing

Free Tier Row Reads/Month
type: PropertyValue
value reference: Quotas

Global Edge Locations
type: PropertyValue
value reference: Infrastructure

OLAP Query Speed (1GB dataset)
type: PropertyValue
value reference: Performance

Replication Latency
type: PropertyValue
value reference: Performance

Supported Languages
type: PropertyValue
value reference: Localization

Installation Required
type: PropertyValue
value reference: Setup

Setup Time (fresh install to first query)
type: PropertyValue
value reference: Operational

Minimum Memory Requirement
type: PropertyValue
value reference: Resources

Single Query Latency (10GB dataset)
type: PropertyValue
value reference: Performance

Maximum Practical Data Scale
type: PropertyValue
value reference: Scalability

Supported SQL Features
type: PropertyValue
value reference: Features

Community Contributors (2025)
type: PropertyValue
value reference: Community

GitHub Stars
type: PropertyValue
value reference: Adoption & Community

Time to Learn (for SQL users)
type: PropertyValue
value reference: Learning

Ingestion Rate (events/second)
type: PropertyValue
value reference: Performance

Query Latency (1B rows)
type: PropertyValue
value reference: Performance

Maximum Recommended Dataset Size
type: PropertyValue
value reference: Performance

Deployment Time
type: PropertyValue
value reference: Performance

Minimum Cluster Size
type: PropertyValue
value reference: Scalability

Memory Per Node
type: PropertyValue
value reference: Resource Efficiency

Multi-node Support
type: PropertyValue
value reference: Architecture

Real-time Upsert Support
type: PropertyValue
value reference: Features

Query Speed (1GB CSV aggregation)
type: PropertyValue
value reference: Performance

Maximum Practical Dataset Size
type: PropertyValue
value reference: Scalability

Memory Usage (1GB CSV load)
type: PropertyValue
value reference: Efficiency

Built-in Statistical Functions
type: PropertyValue
value reference: Features

SQL Support Level
type: PropertyValue
value reference: Query Language

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

Stack Overflow Questions Answered
type: PropertyValue
value reference: Community

First Release Year
type: PropertyValue
value reference: Maturity

Minimum Hardware Requirements
type: PropertyValue
value reference: Infrastructure

Query Latency on 100GB Dataset
type: PropertyValue
value reference: Performance

Memory Usage for 10GB Query
type: PropertyValue
value reference: Efficiency

Time to First Query (fresh install)
type: PropertyValue
value reference: Setup

Number of Supported Languages
type: PropertyValue
value reference: Compatibility

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

Query Processing Throughput (GBps)
type: PropertyValue
value reference: Performance

Setup Time
type: PropertyValue
value reference: Developer Experience

Maximum Dataset Size
type: PropertyValue
value reference: Scalability

Query Latency (1B rows, COUNT aggregation)
type: PropertyValue
value reference: Performance

Data Compression Ratio
type: PropertyValue
value reference: Storage Efficiency

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

License Restrictions
type: PropertyValue
value reference: Licensing

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

Installation Size
type: PropertyValue
value reference: Resource Footprint

SQL Standard Compatibility
type: PropertyValue
value reference: Compatibility

Multi-node Replication
type: PropertyValue
value reference: Clustering

Operational Complexity
type: PropertyValue
value reference: Operations

P99 Query Latency (1B rows, aggregation)
type: PropertyValue
value reference: Performance

Ingestion Latency (Kafka to query-ready)
type: PropertyValue
value reference: Real-time Capability

SQL Compliance Level
type: PropertyValue
value reference: Developer Experience

Maximum Recommended Node Storage
type: PropertyValue
value reference: Scalability

Native Streaming Sources
type: PropertyValue
value reference: Integration

Enterprise Support Availability
type: PropertyValue
value reference: Support & Licensing

Query Latency (1 billion rows)
type: PropertyValue
value reference: Performance

Monthly Cost (100 GB compressed)
type: PropertyValue
value reference: Pricing

Ingestion Throughput
type: PropertyValue
value reference: Performance

Data Retention for Time-Travel
type: PropertyValue
value reference: Features

Compression Ratio
type: PropertyValue
value reference: Storage

Licensing Model
type: PropertyValue
value reference: Legal & Cost

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

Ingestion Latency (end-to-end)
type: PropertyValue
value reference: Real-time Performance

Memory Usage per Query
type: PropertyValue
value reference: Efficiency

Native SQL Support
type: PropertyValue
value reference: Querying

Multi-tenancy Isolation
type: PropertyValue
value reference: Architecture

Typical Cost per TB/year
type: PropertyValue
value reference: Economics

Ingestion Latency
type: PropertyValue
value reference: Performance

Query Latency (100M rows)
type: PropertyValue
value reference: Performance

Maximum Cluster Nodes
type: PropertyValue
value reference: Scalability

Streaming Integration
type: PropertyValue
value reference: Features

Transaction Support
type: PropertyValue
value reference: Features

Typical Storage Cost
type: PropertyValue
value reference: Cost

Max Recommended Dataset Size
type: PropertyValue
value reference: Scalability

SQL Feature Completeness
type: PropertyValue
value reference: Features

Time-Series Aggregation Support
type: PropertyValue
value reference: Features

Max Ingestion Throughput
type: PropertyValue
value reference: Performance

Storage Cost per TB/month
type: PropertyValue
value reference: Pricing

Typical Node Memory
type: PropertyValue
value reference: Infrastructure

Minimum Recommended Cluster Size
type: PropertyValue
value reference: Deployment

Max Dataset Size (Practical)
type: PropertyValue
value reference: Scalability

Query Latency (1B row scan, 10 column aggregate)
type: PropertyValue
value reference: Performance

Storage Cost (per TB/month)
type: PropertyValue
value reference: Cost

Typical Data Compression Ratio
type: PropertyValue
value reference: Storage Efficiency

Minimum Cluster Size (nodes)
type: PropertyValue
value reference: Infrastructure

Max Concurrent Queries (default config)
type: PropertyValue
value reference: Throughput

Data Ingestion Latency
type: PropertyValue
value reference: Performance

AWS Service Integration (native)
type: PropertyValue
value reference: Ecosystem

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

Query Latency (1 billion rows, simple SELECT)
type: PropertyValue
value reference: Performance

Cost per GB Scanned
type: PropertyValue
value reference: Pricing

Maximum Ingestion Rate
type: PropertyValue
value reference: Data Ingestion

Infrastructure Management Overhead
type: PropertyValue
value reference: Operations

Minimum Monthly Cost (basic setup)
type: PropertyValue
value reference: Pricing

Cloud Provider Support
type: PropertyValue
value reference: Infrastructure

Automatic Scaling Time
type: PropertyValue
value reference: Performance

SQL Compatibility
type: PropertyValue
value reference: Features

Average Query Latency (1 Billion Row Scan)
type: PropertyValue
value reference: Performance

Monthly Cost per TB Stored
type: PropertyValue
value reference: Cost

Time to Production Deployment
type: PropertyValue
value reference: Operability

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: User Experience

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

Peak Ingestion Speed
type: PropertyValue
value reference: Data Ingestion

ANSI SQL Compliance
type: PropertyValue
value reference: SQL Support

Deployment Components
type: PropertyValue
value reference: Operational Complexity

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

Average Query Latency (Standard Aggregation)
type: PropertyValue
value reference: Performance

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

Memory Per 1TB Data
type: PropertyValue
value reference: Resource Requirements

Cluster Node Types Required
type: PropertyValue
value reference: Operational Complexity

Kafka Integration Latency
type: PropertyValue
value reference: Streaming