ClickHouse vs Apache Pinot
type: WebPage
description: ClickHouse excels at real-time OLAP analytics with superior compression and faster query performance on large datasets, while Apache Pinot specializes in low-latency dimensional analytics with better support for streaming data ingestion and complex aggregations at scale.
language: en-US
is accessible for free: true
conditions of access: Free
is part of: website
date published: 2026-07-09T11:39:49.417Z
date created: 2026-07-09T11:39:49.417Z
date modified: 2026-07-09T11:39:49.465Z
primary image of page: https://www.aversusb.net/compare/clickhouse-vs-pinot)#primaryImage
breadcrumb: BreadcrumbList
  item list element: Home
    type: ListItem
    position: 1
    item: Home
  item list element: Compare
    type: ListItem
    position: 2
    item: Compare
  item list element: ClickHouse vs Apache Pinot
    type: ListItem
    position: 3
    item: ClickHouse vs Apache Pinot
speakable: SpeakableSpecification
  css selector: #short-answer
  css selector: #verdict
  css selector: #key-differences

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

Home
type: WebPage

Compare
type: WebPage

ClickHouse vs Apache Pinot
type: Article
type: TechArticle
abstract: ClickHouse excels at real-time OLAP analytics with superior compression and faster query performance on large datasets, while Apache Pinot specializes in low-latency dimensional analytics with better support for streaming data ingestion and complex aggregations at scale.
description: ClickHouse excels at real-time OLAP analytics with superior compression and faster query performance on large datasets, while Apache Pinot specializes in low-latency dimensional analytics with better support for streaming data ingestion and complex aggregations at scale.
language: en-US
main entity of page: ClickHouse vs Apache Pinot
content reference time: 2026-07-09T11:39:49.465Z
author: A Versus B
publisher: A Versus B
date published: 2026-07-09T11:39:49.417Z
date created: 2026-07-09T11:39:49.417Z
date modified: 2026-07-09T11:39:49.465Z
text: Choose ClickHouse if you need maximum query performance, superior compression for cost-efficiency, and can work with its SQL dialect for batch-oriented analytics at petabyte scale. Choose Apache Pinot if you require sub-100ms latency for real-time streaming dashboards, standard SQL compliance, and native Kafka/Pulsar integration with active vendor support.
genre: Software
potential action: ReadAction
  target: ClickHouse vs Apache Pinot
potential action: Compare ClickHouse vs Apache Pinot
  type: Action
  additional type: CompareAction
  target: ClickHouse vs Apache Pinot
  object: ClickHouse
  object: Apache Pinot
about: ClickHouse
about: Apache Pinot
mentions: Query Latency (P99 on 1B rows)
mentions: Data Compression Ratio
mentions: Streaming Ingestion Native Support
mentions: SQL Dialect Compatibility
mentions: Storage Per Node (Typical)
mentions: Community Adoption (GitHub Stars 2026)
mentions: Enterprise Support Availability
related link: https://www.aversusb.net/compare/clickhouse-vs-pinot
related link: https://www.aversusb.net/compare/pinot-vs-clickhouse)
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-druid
related link: https://www.aversusb.net/compare/druid-vs-pinot
related link: https://www.aversusb.net/compare/bigquery-vs-pinot
related link: https://www.aversusb.net/compare/pinot-vs-elasticsearch
citation: ClickHouse — Wikipedia
citation: Apache Pinot — Wikipedia
significant link: https://www.aversusb.net/entity/clickhouse
significant link: https://www.aversusb.net/alternatives/clickhouse
significant link: https://www.aversusb.net/entity/apache-pinot
significant link: https://www.aversusb.net/alternatives/apache-pinot
significant link: https://www.aversusb.net/api/answer/clickhouse-vs-pinot)
significant link: https://www.aversusb.net/api/knowledge-graph/clickhouse-vs-pinot)

A Versus B
type: Organization

ClickHouse
type: SoftwareApplication
description: Distributed columnar OLAP database designed for petabyte-scale real-time analytics
alternate name: Clickhouse
language: en-US
image: ImageObject
  caption: ClickHouse
subject of: ClickHouse vs Apache Pinot

Apache Pinot
type: SoftwareApplication
description: Real-time OLAP engine optimized for low-latency dimensional analytics on streaming data.
alternate name: AP
language: en-US
image: ImageObject
  caption: Apache Pinot
subject of: ClickHouse vs Apache Pinot

ClickHouse vs Apache Pinot — Comparison Data
type: Dataset
description: Structured comparison data for ClickHouse vs Apache Pinot with 164 attributes.
language: en-US
license: https://creativecommons.org/licenses/by/4.0/
creator: A Versus B
distribution: Schema.org JSON-LD (pure)
  type: DataDownload
  encoding format: application/ld+json
distribution: JSON-LD knowledge graph
  type: DataDownload
  encoding format: application/ld+json
distribution: Raw comparison JSON
  type: DataDownload
  encoding format: application/json
distribution: AI Answer API (citation-ready)
  type: DataDownload
  encoding format: application/json
distribution: Structured FAQ pairs JSON
  type: DataDownload
  encoding format: application/json
distribution: Related comparisons JSON
  type: DataDownload
  encoding format: application/json
variable measured: P99 Query Latency (1B rows, aggregation)
  type: PropertyValue
  value reference: Performance
variable measured: Ingestion Latency (Kafka to query-ready)
  type: PropertyValue
  value reference: Real-time Capability
variable measured: SQL Compliance Level
  type: PropertyValue
  value reference: Developer Experience
variable measured: Maximum Recommended Node Storage
  type: PropertyValue
  value reference: Scalability
variable measured: Native Streaming Sources
  type: PropertyValue
  value reference: Integration
variable measured: Enterprise Support Availability
  type: PropertyValue
  value reference: Support & Licensing
variable measured: Query Latency (1 billion rows)
  type: PropertyValue
  value reference: Performance
variable measured: Monthly Cost (100 GB compressed)
  type: PropertyValue
  value reference: Pricing
variable measured: Ingestion Throughput
  type: PropertyValue
  value reference: Performance
variable measured: Data Retention for Time-Travel
  type: PropertyValue
  value reference: Features
variable measured: Compression Ratio
  type: PropertyValue
  value reference: Storage
variable measured: Licensing Model
  type: PropertyValue
  value reference: Economics
variable measured: Learning Curve (1-10 scale)
  type: PropertyValue
  value reference: Usability
variable measured: Query Latency (1GB aggregation)
  type: PropertyValue
  value reference: Performance
variable measured: Compression Ratio (typical)
  type: PropertyValue
  value reference: Efficiency
variable measured: Memory Required (minimal)
  type: PropertyValue
  value reference: Resource Usage
variable measured: Ingest Throughput
  type: PropertyValue
  value reference: Performance
variable measured: Setup Time to First Query
  type: PropertyValue
  value reference: Usability
variable measured: SQL Standard Compliance
  type: PropertyValue
  value reference: Compatibility
variable measured: Query Latency (p99)
  type: PropertyValue
  value reference: Performance
variable measured: Ingestion Latency (end-to-end)
  type: PropertyValue
  value reference: Real-time Performance
variable measured: Memory Usage per Query
  type: PropertyValue
  value reference: Efficiency
variable measured: Maximum Cluster Size
  type: PropertyValue
  value reference: Scalability
variable measured: Native SQL Support
  type: PropertyValue
  value reference: Querying
variable measured: Multi-tenancy Isolation
  type: PropertyValue
  value reference: Architecture
variable measured: Typical Cost per TB/year
  type: PropertyValue
  value reference: Economics
variable measured: Ingestion Latency
  type: PropertyValue
  value reference: Performance
variable measured: Query Latency (100M rows)
  type: PropertyValue
  value reference: Performance
variable measured: Maximum Cluster Nodes
  type: PropertyValue
  value reference: Scalability
variable measured: Streaming Integration
  type: PropertyValue
  value reference: Features
variable measured: Transaction Support
  type: PropertyValue
  value reference: Features
variable measured: GitHub Stars (2026)
  type: PropertyValue
  value reference: Community
variable measured: Typical Maximum Dataset Size
  type: PropertyValue
  value reference: Scalability
variable measured: Idle Memory Usage
  type: PropertyValue
  value reference: Performance
variable measured: Supported Data Formats
  type: PropertyValue
  value reference: Compatibility
variable measured: Query Latency (100M rows, simple aggregation)
  type: PropertyValue
  value reference: Performance
variable measured: Typical Storage Cost
  type: PropertyValue
  value reference: Cost
variable measured: Max Recommended Dataset Size
  type: PropertyValue
  value reference: Scalability
variable measured: SQL Feature Completeness
  type: PropertyValue
  value reference: Features
variable measured: Time-Series Aggregation Support
  type: PropertyValue
  value reference: Features
variable measured: Max Ingestion Throughput
  type: PropertyValue
  value reference: Performance
variable measured: Storage Cost per TB/month
  type: PropertyValue
  value reference: Pricing
variable measured: Typical Node Memory
  type: PropertyValue
  value reference: Infrastructure
variable measured: Minimum Recommended Cluster Size
  type: PropertyValue
  value reference: Deployment
variable measured: Max Dataset Size (Practical)
  type: PropertyValue
  value reference: Scalability
variable measured: Query Latency (1B row scan, 10 column aggregate)
  type: PropertyValue
  value reference: Performance
variable measured: Storage Cost (per TB/month)
  type: PropertyValue
  value reference: Cost
variable measured: Typical Data Compression Ratio
  type: PropertyValue
  value reference: Storage Efficiency
variable measured: Minimum Cluster Size (nodes)
  type: PropertyValue
  value reference: Infrastructure
variable measured: Max Concurrent Queries (default config)
  type: PropertyValue
  value reference: Throughput
variable measured: Data Ingestion Latency
  type: PropertyValue
  value reference: Performance
variable measured: AWS Service Integration (native)
  type: PropertyValue
  value reference: Ecosystem
variable measured: GitHub Stars (as of 2026)
  type: PropertyValue
  value reference: Community
variable measured: Query Latency (1 billion rows, simple SELECT)
  type: PropertyValue
  value reference: Performance
variable measured: Cost per GB Scanned
  type: PropertyValue
  value reference: Pricing
variable measured: Maximum Ingestion Rate
  type: PropertyValue
  value reference: Data Ingestion
variable measured: Infrastructure Management Overhead
  type: PropertyValue
  value reference: Operations
variable measured: Minimum Monthly Cost (basic setup)
  type: PropertyValue
  value reference: Pricing
variable measured: Cloud Provider Support
  type: PropertyValue
  value reference: Features
variable measured: Automatic Scaling Time
variable measured: SQL Compatibility
variable measured: Average Query Latency (1 Billion Row Scan)
variable measured: Monthly Cost per TB Stored
variable measured: Time to Production Deployment
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)

ClickHouse vs Apache Pinot — Attribute Category Vocabulary
type: DefinedTermSet
language: en-US
description: Taxonomy of attribute categories used to classify comparison data for ClickHouse vs Apache Pinot.
has defined term: Performance
has defined term: Real-time Capability
has defined term: Developer Experience
has defined term: Scalability
has defined term: Integration
has defined term: Support & Licensing
has defined term: Pricing
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: Compatibility
has defined term: Real-time Performance
has defined term: Querying
has defined term: Architecture
has defined term: Community
has defined term: Cost
has defined term: Infrastructure
has defined term: Deployment
has defined term: Storage Efficiency
has defined term: Throughput
has defined term: Ecosystem
has defined term: Data Ingestion
has defined term: Operations
has defined term: Setup
has defined term: Reliability
has defined term: Development Efficiency
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
has defined term: Maturity
has defined term: Licensing
has defined term: Resource Efficiency
has defined term: Query Features
has defined term: Market Position
has defined term: Total Cost
has defined term: Ease of Use
has defined term: Query Language
has defined term: Functionality
has defined term: Collaboration
has defined term: Data Pipeline
has defined term: Search Capability
has defined term: Capability
has defined term: Ingestion

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Development Efficiency
type: DefinedTerm
term code: development-efficiency
in defined term set: ClickHouse vs Apache Pinot — Attribute Category Vocabulary

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

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

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

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

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

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

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

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

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

Query Features
type: DefinedTerm
term code: query-features
in defined term set: ClickHouse vs Apache Pinot — Attribute Category Vocabulary

Market Position
type: DefinedTerm
term code: market-position
in defined term set: ClickHouse vs Apache Pinot — Attribute Category Vocabulary

Total Cost
type: DefinedTerm
term code: total-cost
in defined term set: ClickHouse vs Apache Pinot — Attribute Category Vocabulary

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

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

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

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

Data Pipeline
type: DefinedTerm
term code: data-pipeline
in defined term set: ClickHouse vs Apache Pinot — Attribute Category Vocabulary

Search Capability
type: DefinedTerm
term code: search-capability
in defined term set: ClickHouse vs Apache Pinot — Attribute Category Vocabulary

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

Ingestion
type: DefinedTerm
term code: ingestion
in defined term set: ClickHouse vs Apache Pinot — Attribute Category Vocabulary

faq
type: FAQPage
language: en-US
is accessible for free: true
conditions of access: Free
date modified: 2026-07-09T11:39:49.465Z
author: A Versus B
publisher: A Versus B
is part of: ClickHouse vs Apache Pinot
main entity: Which database is faster for analytical queries?
  type: Question
  accepted answer: Answer
    text: ClickHouse typically achieves 50-200ms P99 latency on billion-row aggregations due to superior columnar compression and vectorized execution, compared to Pinot's 100-500ms. However, Pinot excels at streaming ingestion latency (sub-second vs ClickHouse's 5-30 seconds), making Pinot better for real-time dashboard freshness.
    language: en-US
main entity: How much storage will each require for 100GB of raw data?
  type: Question
  accepted answer: Answer
    text: ClickHouse with 30:1 compression would need ~3.3TB, while Pinot with 6:1 compression would need ~16.7TB. ClickHouse's superior compression saves approximately 80% storage costs, but requires more CPU for decompression during queries. For cost-sensitive workloads processing cold historical data, ClickHouse wins; for real-time systems with frequent updates, Pinot's lower compression overhead may be acceptable.
    language: en-US
main entity: Can I use standard SQL with both databases?
  type: Question
  accepted answer: Answer
    text: Apache Pinot supports standard ANSI SQL directly, allowing teams to use existing SQL expertise immediately. ClickHouse uses a SQL variant with proprietary functions (arrayMap, groupArray, etc.), requiring 2-4 weeks of developer ramp-up. Teams with large existing SQL codebases should choose Pinot; new projects can optimize for ClickHouse's superior performance.
    language: en-US
main entity: Which is better for real-time streaming dashboards?
  type: Question
  accepted answer: Answer
    text: Apache Pinot is purpose-built for this with native Kafka/Pulsar support achieving sub-second ingestion-to-query latency and StarTree vendor SLAs. ClickHouse's 5-30 second ingestion delay and basic Kafka integration make it unsuitable for sub-100ms dashboard refresh requirements. Choose Pinot if your product requires real-time user-facing dashboards.
    language: en-US
main entity: What are the deployment differences?
  type: Question
  accepted answer: Answer
    text: ClickHouse scales vertically with single nodes handling 2-10TB, ideal for consolidated analytics infrastructure. Pinot requires horizontal distribution, with each node holding 0.5-2TB, making it better for distributed cloud deployments. ClickHouse is simpler to operate (fewer nodes); Pinot requires orchestration expertise but provides better fault tolerance across regions.
    language: en-US

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: Setup

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: Development Efficiency

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

First Release Year
type: PropertyValue
value reference: Maturity

Setup Time
type: PropertyValue
value reference: Operations

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

Operational Complexity
type: PropertyValue
value reference: Operations

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

License Restrictions
type: PropertyValue
value reference: Licensing

Query Latency (1B rows, 100 dimensions)
type: PropertyValue
value reference: Performance

Memory Footprint per 1GB Data
type: PropertyValue
value reference: Resource Efficiency

Maximum Events/Sec per Node
type: PropertyValue
value reference: Throughput

Typical Cluster Setup Cost
type: PropertyValue
value reference: Economics

Multi-table JOIN Support
type: PropertyValue
value reference: Query Features

Enterprise Deployments
type: PropertyValue
value reference: Market Position

Query Latency (p95 on Real-Time Data)
type: PropertyValue
value reference: Performance

Minimum Cluster Size for 1TB Dataset
type: PropertyValue
value reference: Infrastructure

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

Storage Compression Ratio
type: PropertyValue
value reference: Storage

Typical Use Case Flexibility
type: PropertyValue
value reference: Features

JOIN Operation Support
type: PropertyValue
value reference: Features

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

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

Setup Time to Production
type: PropertyValue
value reference: Deployment

Events/Second Ingestion
type: PropertyValue
value reference: Throughput

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

Maximum Recommended Cluster Size
type: PropertyValue
value reference: Scalability

Full-Text Search Capability
type: PropertyValue
value reference: Features

Time to First Production Query
type: PropertyValue
value reference: Ease of Use

SQL Support
type: PropertyValue
value reference: Query Language

Typical Memory Per Node
type: PropertyValue
value reference: Resource Efficiency

Setup Time (Minutes)
type: PropertyValue
value reference: Ease of Use

Query Latency on 1GB Dataset
type: PropertyValue
value reference: Performance

Maximum Scalable Dataset Size
type: PropertyValue
value reference: Scalability

Minimum Cluster Nodes Required
type: PropertyValue
value reference: Infrastructure

Real-time Streaming Ingestion
type: PropertyValue
value reference: Features

Concurrent Queries Supported
type: PropertyValue
value reference: Performance

Supported Programming Languages
type: PropertyValue
value reference: Functionality

Annual Infrastructure Cost (1TB dataset)
type: PropertyValue
value reference: Cost

Concurrent User Support
type: PropertyValue
value reference: Collaboration

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

Data Freshness
type: PropertyValue
value reference: Data Pipeline

License Type
type: PropertyValue
value reference: Licensing

Deployment Flexibility
type: PropertyValue
value reference: Architecture

Ingestion Streaming Support
type: PropertyValue
value reference: Data Pipeline

Base Monthly Cost (Small Cluster)
type: PropertyValue
value reference: Cost

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

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: Performance

Concurrent Users Supported
type: PropertyValue
value reference: Scalability

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: Infrastructure

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

Typical Query Latency (1B rows, GROUP BY)
type: PropertyValue
value reference: Performance

Index Size to Data Ratio
type: PropertyValue
value reference: Storage Efficiency

Full-Text Search Optimization
type: PropertyValue
value reference: Search Capability

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

Real-Time Ingestion Support
type: PropertyValue
value reference: Data Ingestion

Typical Deployment Complexity
type: PropertyValue
value reference: Operations

Maximum Practical Dataset Size
type: PropertyValue
value reference: Scalability

SQL Query Support
type: PropertyValue
value reference: Capability

Query Latency (Typical Analytical Query)
type: PropertyValue
value reference: Performance

Data Ingestion Throughput
type: PropertyValue
value reference: Performance

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

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

Maximum Table Size
type: PropertyValue
value reference: Scalability

Deployment Options
type: PropertyValue
value reference: Infrastructure

P99 Query Latency
type: PropertyValue
value reference: Performance

Streaming Ingestion Rate
type: PropertyValue
value reference: Ingestion

Aggregation Query Throughput
type: PropertyValue
value reference: Performance

Operational Components
type: PropertyValue
value reference: Operations

High-Cardinality Dimension Support
type: PropertyValue
value reference: Features

Segment Size (typical)
type: PropertyValue
value reference: Storage

Learning Curve (Complexity)
type: PropertyValue
value reference: Operations