Pinot vs DuckDB
type: Article
description: Pinot is a distributed OLAP database designed for real-time analytics at scale across multiple servers, while DuckDB is an embedded SQL database optimized for fast in-process analytics on single machines. Pinot excels with massive datasets and continuous ingestion; DuckDB prioritizes simplicity and query speed on local data.
language: en-US
date published: 2026-07-08T12:32:43.964Z
date created: 2026-07-08T12:32:43.964Z
date modified: 2026-07-08T12:32:44.014Z
content reference time: 2026-07-08T12:32:44.014Z
author: A Versus B
publisher: A Versus B
about: Apache Pinot
about: DuckDB
abstract: Pinot is a distributed OLAP database designed for real-time analytics at scale across multiple servers, while DuckDB is an embedded SQL database optimized for fast in-process analytics on single machines. Pinot excels with massive datasets and continuous ingestion; DuckDB prioritizes simplicity and query speed on local data.
text: Architecture. Deployment Complexity. Real-time Ingestion Rate. Query Performance (1B rows). Scalability. Operational Overhead. Use Case Focus
conclusion text: Choose Pinot if you need to ingest millions of events per second continuously, serve sub-second queries on petabyte-scale data across distributed infrastructure, and run 24/7 production analytics systems (typical for LinkedIn-scale applications). Choose DuckDB if you prioritize simplicity, work with datasets under 1TB, need zero operational overhead, and want to embed SQL analytics directly into Python/R/Node.js applications or perform fast ad-hoc data exploration.
additional property: Query Latency (1B rows, 100 dimensions)
  type: PropertyValue
  value: Apache Pinot: 50-100ms | DuckDB: N/A
additional property: Memory Footprint per 1GB Data
  type: PropertyValue
  value: Apache Pinot: 150-300MB | DuckDB: N/A
additional property: Maximum Events/Sec per Node
  type: PropertyValue
  value: Apache Pinot: 10K-50K | DuckDB: N/A
additional property: Typical Cluster Setup Cost
  type: PropertyValue
  value: Apache Pinot: $1500-3000 | DuckDB: N/A
additional property: Multi-table JOIN Support
  type: PropertyValue
  value: Apache Pinot: Full support (INNER, LEFT, RIGHT, FULL) | DuckDB: N/A
additional property: SQL Compatibility
  type: PropertyValue
  value: Apache Pinot: PQL + Limited SQL (60% compatibility) | DuckDB: N/A
additional property: Enterprise Deployments
  type: PropertyValue
  value: Apache Pinot: 1000+ (LinkedIn, Uber, etc) | DuckDB: N/A
additional property: Data Compression Ratio
  type: PropertyValue
  value: Apache Pinot: 8-10x | DuckDB: 5-8x
  value reference: Apache Pinot
additional property: Ingestion Latency (end-to-end)
  type: PropertyValue
  value: Apache Pinot: 100-500ms | DuckDB: N/A
additional property: Memory Usage per Query
  type: PropertyValue
  value: Apache Pinot: 100-400MB | DuckDB: N/A
additional property: Native SQL Support
  type: PropertyValue
  value: Apache Pinot: PQL (Custom) + Presto Bridge | DuckDB: N/A
additional property: Multi-tenancy Isolation
  type: PropertyValue
  value: Apache Pinot: Native tenant isolation | DuckDB: N/A
additional property: Typical Cost per TB/year
  type: PropertyValue
  value: Apache Pinot: $2000-3500 | DuckDB: N/A
additional property: Query Latency (p95 on Real-Time Data)
  type: PropertyValue
  value: Apache Pinot: 500-2000ms | DuckDB: N/A
additional property: Data Ingestion Rate
  type: PropertyValue
  value: Apache Pinot: 500,000-1,000,000 | DuckDB: N/A
additional property: Minimum Cluster Size for 1TB Dataset
  type: PropertyValue
  value: Apache Pinot: 5-8 nodes | DuckDB: N/A
additional property: GitHub Stars (Community Activity)
  type: PropertyValue
  value: Apache Pinot: 5,300 | DuckDB: N/A
additional property: Storage Compression Ratio
  type: PropertyValue
  value: Apache Pinot: ~4-6x columnar | DuckDB: N/A
additional property: Typical Use Case Flexibility
  type: PropertyValue
  value: Apache Pinot: Ad-hoc queries (generalized) | DuckDB: N/A
additional property: JOIN Operation Support
  type: PropertyValue
  value: Apache Pinot: Full support | DuckDB: N/A
additional property: Max Ingestion Throughput
  type: PropertyValue
  value: Apache Pinot: 1,000,000-2,000,000 events/sec | DuckDB: N/A
additional property: Query Latency (p99)
  type: PropertyValue
  value: Apache Pinot: 100-500ms (real-time) | DuckDB: N/A
additional property: Storage Cost per TB/Month
  type: PropertyValue
  value: Apache Pinot: $200-400 | DuckDB: N/A
additional property: Typical Node Memory
  type: PropertyValue
  value: Apache Pinot: 16-64GB | DuckDB: N/A
additional property: Minimum Recommended Cluster Size
  type: PropertyValue
  value: Apache Pinot: 5-7 nodes (3 controllers + 2-4 brokers) | DuckDB: N/A
additional property: Max Dataset Size (Practical)
  type: PropertyValue
  value: Apache Pinot: 100-500TB (hot data) | DuckDB: N/A
additional property: Query Latency (P95)
  type: PropertyValue
  value: Apache Pinot: 100-500ms | DuckDB: N/A
additional property: Per-Query Cost (1TB scan)
  type: PropertyValue
  value: Apache Pinot: $0 (infrastructure only) | DuckDB: N/A
additional property: Data Ingestion Latency
  type: PropertyValue
  value: Apache Pinot: 0.1 (streaming) | DuckDB: N/A
additional property: Setup Time to Production
  type: PropertyValue
  value: Apache Pinot: 12 weeks | DuckDB: N/A
additional property: Maximum Cluster Size
  type: PropertyValue
  value: Apache Pinot: Limited by infrastructure | DuckDB: 1 (single machine)
  value reference: Apache Pinot
additional property: SQL Standard Compliance
  type: PropertyValue
  value: Apache Pinot: ~60% (Pinot Query Language variant) | DuckDB: 95% ANSI SQL
  value reference: DuckDB
additional property: Events/Second Ingestion
  type: PropertyValue
  value: Apache Pinot: 500,000/sec (streaming) | DuckDB: N/A
additional property: Annual TCO (100TB dataset)
  type: PropertyValue
  value: Apache Pinot: $150,000 | DuckDB: N/A
additional property: P99 Query Latency
  type: PropertyValue
  value: Apache Pinot: 50-200ms | DuckDB: N/A
additional property: Maximum Recommended Cluster Size
  type: PropertyValue
  value: Apache Pinot: 500+ (LinkedIn runs 1,000+) | DuckDB: N/A
additional property: Full-Text Search Capability
  type: PropertyValue
  value: Apache Pinot: Limited (phrase queries, basic tokenization) | DuckDB: N/A
additional property: Time to First Production Query
  type: PropertyValue
  value: Apache Pinot: 14-30 days (requires schema design and tuning) | DuckDB: N/A
additional property: SQL Support
  type: PropertyValue
  value: Apache Pinot: Native SQL with PQL extensions (ANSI-compliant subset) | DuckDB: N/A
additional property: Typical Memory Per Node
  type: PropertyValue
  value: Apache Pinot: 16-32GB for analytics workload | DuckDB: N/A
additional property: GitHub Stars (as of 2026)
  type: PropertyValue
  value: Apache Pinot: 8,200+ | DuckDB: N/A
additional property: Setup Time (Minutes)
  type: PropertyValue
  value: Apache Pinot: 240-480 | DuckDB: 5-10
  value reference: DuckDB
additional property: Query Latency on 1GB Dataset
  type: PropertyValue
  value: Apache Pinot: 100-500 | DuckDB: 10-50
  value reference: DuckDB
additional property: Maximum Scalable Dataset Size
  type: PropertyValue
  value: Apache Pinot: 100,000+ | DuckDB: 10-50
  value reference: Apache Pinot
additional property: Minimum Cluster Nodes Required
  type: PropertyValue
  value: Apache Pinot: 5-7 | DuckDB: 1
  value reference: DuckDB
additional property: Real-time Streaming Ingestion
  type: PropertyValue
  value: Apache Pinot: Native (Kafka, S3, MQ) | DuckDB: Batch-focused only
additional property: Concurrent Queries Supported
  type: PropertyValue
  value: Apache Pinot: 1000+ | DuckDB: Limited by single machine
additional property: Supported Programming Languages
  type: PropertyValue
  value: Apache Pinot: Java, Python (limited) | DuckDB: Python, R, Java, C++, Node.js, Go
  value reference: DuckDB
additional property: Annual Infrastructure Cost (1TB dataset)
  type: PropertyValue
  value: Apache Pinot: 50,000-150,000 | DuckDB: 0-5,000
  value reference: DuckDB
interactivity type: active
significant link: https://www.aversusb.net/entity/apache-pinot
significant link: https://www.aversusb.net/alternatives/apache-pinot
significant link: https://www.aversusb.net/entity/duckdb
significant link: https://www.aversusb.net/alternatives/duckdb
significant link: https://www.aversusb.net/api/answer/pinot-vs-duckdb)
significant link: https://www.aversusb.net/api/v1/schema/pinot-vs-duckdb)
related link: https://www.aversusb.net/compare/pinot-vs-duckdb
related link: https://www.aversusb.net/compare/duckdb-vs-pandas)
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/duckdb-vs-sqlite
related link: https://www.aversusb.net/compare/druid-vs-pinot
related link: https://www.aversusb.net/compare/duckdb-vs-spark
related link: https://www.aversusb.net/compare/apache-spark-vs-duckdb
teaches: How to choose between Apache Pinot and DuckDB
genre: Software

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

A Versus B
type: Organization

Apache Pinot
type: SoftwareApplication
alternate name: AP
language: en-US
description: Distributed real-time OLAP database for streaming analytics at scale
image: ImageObject
  caption: Apache Pinot
subject of: Pinot vs DuckDB
image: ImageObject
  caption: Apache Pinot

DuckDB
type: SoftwareApplication
alternate name: Duckdb
language: en-US
description: In-process columnar SQL database for analytical queries and OLAP workloads.
image: ImageObject
  caption: DuckDB
subject of: Pinot vs DuckDB
image: ImageObject
  caption: DuckDB

Pinot vs DuckDB — Structured Comparison Data
type: Dataset
description: Machine-readable comparison dataset for Pinot vs DuckDB. Contains 137 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
  type: DataDownload
  encoding format: application/json
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: Query Latency (1B rows, 100 dimensions)
  type: PropertyValue
  value reference: Performance
variable measured: Memory Footprint per 1GB Data
  type: PropertyValue
  value reference: Resource Efficiency
variable measured: Maximum Events/Sec per Node
  type: PropertyValue
  value reference: Throughput
variable measured: Typical Cluster Setup Cost
  type: PropertyValue
  value reference: Economics
variable measured: Multi-table JOIN Support
  type: PropertyValue
  value reference: Query Features
variable measured: SQL Compatibility
  type: PropertyValue
  value reference: Features
variable measured: Enterprise Deployments
  type: PropertyValue
  value reference: Market Position
variable measured: Data Compression Ratio
  type: PropertyValue
  value reference: Storage Efficiency
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: 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: Query Latency (p95 on Real-Time Data)
  type: PropertyValue
  value reference: Performance
variable measured: Data Ingestion Rate
  type: PropertyValue
  value reference: Performance
variable measured: Minimum Cluster Size for 1TB Dataset
  type: PropertyValue
  value reference: Infrastructure
variable measured: GitHub Stars (Community Activity)
  type: PropertyValue
  value reference: Community
variable measured: Storage Compression Ratio
  type: PropertyValue
  value reference: Performance
variable measured: Typical Use Case Flexibility
  type: PropertyValue
  value reference: Features
variable measured: JOIN Operation Support
  type: PropertyValue
  value reference: Features
variable measured: Max Ingestion Throughput
  type: PropertyValue
  value reference: Performance
variable measured: Query Latency (p99)
  type: PropertyValue
  value reference: Performance
variable measured: Storage Cost per TB/Month
  type: PropertyValue
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variable measured: Typical Node Memory
  type: PropertyValue
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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 (P95)
  type: PropertyValue
  value reference: Performance
variable measured: Per-Query Cost (1TB scan)
  type: PropertyValue
  value reference: Pricing
variable measured: Data Ingestion Latency
  type: PropertyValue
  value reference: Real-time Performance
variable measured: Setup Time to Production
  type: PropertyValue
  value reference: Deployment
variable measured: Maximum Cluster Size
  type: PropertyValue
  value reference: Scalability
variable measured: SQL Standard Compliance
  type: PropertyValue
  value reference: Developer Experience
variable measured: Events/Second Ingestion
  type: PropertyValue
  value reference: Throughput
variable measured: Annual TCO (100TB dataset)
  type: PropertyValue
  value reference: Total Cost
variable measured: P99 Query Latency
  type: PropertyValue
  value reference: Performance
variable measured: Maximum Recommended Cluster Size
  type: PropertyValue
  value reference: Scalability
variable measured: Full-Text Search Capability
  type: PropertyValue
  value reference: Features
variable measured: Time to First Production Query
  type: PropertyValue
  value reference: Ease of Use
variable measured: SQL Support
  type: PropertyValue
  value reference: Query Language
variable measured: Typical Memory Per Node
  type: PropertyValue
  value reference: Resource Efficiency
variable measured: GitHub Stars (as of 2026)
  type: PropertyValue
  value reference: Community Adoption
variable measured: Setup Time (Minutes)
  type: PropertyValue
  value reference: Ease of Use
variable measured: Query Latency on 1GB Dataset
  type: PropertyValue
  value reference: Performance
variable measured: Maximum Scalable Dataset Size
  type: PropertyValue
  value reference: Scalability
variable measured: Minimum Cluster Nodes Required
  type: PropertyValue
  value reference: Infrastructure
variable measured: Real-time Streaming Ingestion
  type: PropertyValue
  value reference: Features
variable measured: Concurrent Queries Supported
  type: PropertyValue
  value reference: Performance
variable measured: Supported Programming Languages
  type: PropertyValue
  value reference: Language Support
variable measured: Annual Infrastructure Cost (1TB dataset)
  type: PropertyValue
  value reference: Cost
variable measured: Concurrent User Support
  type: PropertyValue
  value reference: Collaboration
variable measured: Query Latency (Average)
  type: PropertyValue
  value reference: Performance
variable measured: Data Freshness
  type: PropertyValue
  value reference: Data Pipeline
variable measured: License Type
  type: PropertyValue
  value reference: Licensing
variable measured: Deployment Flexibility
  type: PropertyValue
  value reference: Infrastructure
variable measured: Ingestion Streaming Support
  type: PropertyValue
  value reference: Data Pipeline
variable measured: Base Monthly Cost (Small Cluster)
  type: PropertyValue
  value reference: Cost
variable measured: Query Latency (Median)
  type: PropertyValue
  value reference: Performance
variable measured: Streaming Ingestion Latency
  type: PropertyValue
  value reference: Real-time Capability
variable measured: On-Demand Query Pricing
  type: PropertyValue
  value reference: Cost
variable measured: Infrastructure Management
  type: PropertyValue
  value reference: Operations
variable measured: Maximum Daily Event Throughput
variable measured: Time to Deploy
variable measured: Concurrent Users Supported
variable measured: Ingestion Rate (events/second)
variable measured: Query Latency (1B rows)
variable measured: Maximum Recommended Dataset Size
variable measured: Deployment Time
variable measured: Minimum Cluster Size
variable measured: Memory Per Node
is based on: https://www.aversusb.net/compare/pinot-vs-duckdb)

Pinot vs DuckDB — Attribute Category Vocabulary
type: DefinedTermSet
language: en-US
description: Taxonomy of attribute categories used to classify comparison data for Pinot vs DuckDB.
has defined term: Performance
has defined term: Resource Efficiency
has defined term: Throughput
has defined term: Economics
has defined term: Query Features
has defined term: Features
has defined term: Market Position
has defined term: Storage Efficiency
has defined term: Real-time Performance
has defined term: Efficiency
has defined term: Querying
has defined term: Architecture
has defined term: Infrastructure
has defined term: Community
has defined term: Cost
has defined term: Deployment
has defined term: Scalability
has defined term: Pricing
has defined term: Developer Experience
has defined term: Total Cost
has defined term: Ease of Use
has defined term: Query Language
has defined term: Community Adoption
has defined term: Language Support
has defined term: Collaboration
has defined term: Data Pipeline
has defined term: Licensing
has defined term: Real-time Capability
has defined term: Operations
has defined term: Time to Value
has defined term: Complexity
has defined term: Resource Usage
has defined term: Reliability
has defined term: Concurrency
has defined term: Maturity
has defined term: Adoption
has defined term: Compatibility
has defined term: Feature Completeness
has defined term: Data Integrity
has defined term: Implementation
has defined term: Ecosystem
has defined term: API Completeness
has defined term: Community Support
has defined term: SQL Features
has defined term: Workflow Speed
has defined term: Quotas
has defined term: Global Presence
has defined term: Accessibility
has defined term: Convenience
has defined term: Usability

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Language Support
type: DefinedTerm
term code: language-support
in defined term set: Pinot vs DuckDB — Attribute Category Vocabulary

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

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

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

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

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

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

Complexity
type: DefinedTerm
term code: complexity
in defined term set: Pinot vs DuckDB — Attribute Category Vocabulary

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Global Presence
type: DefinedTerm
term code: global-presence
in defined term set: Pinot vs DuckDB — Attribute Category Vocabulary

Accessibility
type: DefinedTerm
term code: accessibility
in defined term set: Pinot vs DuckDB — Attribute Category Vocabulary

Convenience
type: DefinedTerm
term code: convenience
in defined term set: Pinot vs DuckDB — Attribute Category Vocabulary

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

faq
type: FAQPage
language: en-US
is accessible for free: true
conditions of access: Free
date modified: 2026-07-08T12:32:44.014Z
author: A Versus B
publisher: A Versus B
is part of: pinot-vs-duckdb)
main entity: When should I use Pinot over DuckDB?
  type: Question
  accepted answer: Answer
    text: Use Pinot when you need to ingest 1M+ events per second continuously, serve sub-second queries on datasets exceeding 1TB, or require 24/7 production analytics systems with high availability. Pinot's distributed architecture handles massive scale; DuckDB saturates at typical RAM limits (1-2TB). Companies like LinkedIn process 130+ trillion events daily with Pinot.
    language: en-US
main entity: Is DuckDB a Pinot replacement?
  type: Question
  accepted answer: Answer
    text: No. DuckDB replaces single-node analytical databases (SQLite, in-memory pandas) and excels for exploratory analytics, BI queries, and embedded analytics. Pinot replaces data warehouses and real-time analytics systems. DuckDB's 1TB limit and lack of real-time ingestion make it unsuitable for enterprise streaming use cases.
    language: en-US
main entity: What are the total costs: Pinot vs DuckDB?
  type: Question
  accepted answer: Answer
    text: DuckDB: $0 (open-source, self-hosted). Pinot infrastructure: 4-node cluster costs ~$3,000-5,000/month (AWS m5.2xlarge × 4 + Zookeeper). However, Pinot's handling of massive scale eliminates need for secondary caching layers, and its real-time capability prevents costly ETL pipeline delays. ROI depends on query volume and data velocity.
    language: en-US
main entity: Can DuckDB handle streaming data?
  type: Question
  accepted answer: Answer
    text: DuckDB is not designed for continuous streaming. While you can periodically ingest new files (every 1-5 minutes), it lacks Pinot's streaming ingestion pipelines, watermarking, and late-arrival data handling. For true real-time analytics (sub-second latency with continuous updates), Pinot is required.
    language: en-US
main entity: How does query performance compare on 100GB datasets?
  type: Question
  accepted answer: Answer
    text: On 100GB in-memory: DuckDB averages 0.5-1.5 seconds due to vectorized execution and aggressive optimization. Pinot: 1-3 seconds including distributed query coordination overhead. DuckDB wins on latency, but Pinot maintains consistency as data scales to 10TB+. At 1TB+, Pinot's distributed query execution becomes advantageous.
    language: en-US

How to Choose Between Apache Pinot and DuckDB
type: HowTo
description: Pinot is a distributed OLAP database designed for real-time analytics at scale across multiple servers, while DuckDB is an embedded SQL database optimized for fast in-process analytics on single machines. Pinot excels with massive datasets and continuous ingestion; DuckDB prioritizes simplicity and query speed on local data.
language: en-US
total time: PT3M
step: Consider: Architecture
step: Consider: Deployment Complexity
step: Consider: Real-time Ingestion Rate
step: Consider: Query Performance (1B rows)
step: Consider: Scalability
step: Consider: Operational Overhead
step: Consider: Use Case Focus
tool: A Versus B Comparison Guide
tip: HowToTip
  text: Choose Pinot if you need to ingest millions of events per second continuously, serve sub-second queries on petabyte-scale data across distributed infrastructure, and run 24/7 production analytics systems (typical for LinkedIn-scale applications). Choose DuckDB if you prioritize simplicity, work with datasets under 1TB, need zero operational overhead, and want to embed SQL analytics directly into Python/R/Node.js applications or perform fast ad-hoc data exploration.

Consider: Architecture
type: HowToStep
position: 1
text: Architecture: Apache Pinot has Distributed, multi-node cluster, while DuckDB has Embedded, single-process.

Consider: Deployment Complexity
type: HowToStep
position: 2
text: Deployment Complexity: Apache Pinot has Requires cluster setup, Zookeeper coordination, 6+ months typical implementation, while DuckDB has Single library import, 5-minute setup.

Consider: Real-time Ingestion Rate
type: HowToStep
position: 3
text: Real-time Ingestion Rate: Apache Pinot has 1M+ events/second at scale, while DuckDB has 10k-100k events/second (batch optimized).

Consider: Query Performance (1B rows)
type: HowToStep
position: 4
text: Query Performance (1B rows): Apache Pinot has 2-5 seconds via distributed execution, while DuckDB has 0.5-2 seconds (in-memory, single machine).

Consider: Scalability
type: HowToStep
position: 5
text: Scalability: Apache Pinot has Horizontal: add nodes for 10TB+ datasets, while DuckDB has Vertical: limited by available RAM (typically 1TB).

Consider: Operational Overhead
type: HowToStep
position: 6
text: Operational Overhead: Apache Pinot has High: cluster monitoring, rebalancing, failover management, while DuckDB has Minimal: no infrastructure dependencies.

Consider: Use Case Focus
type: HowToStep
position: 7
text: Use Case Focus: Apache Pinot has 24/7 streaming analytics at enterprise scale, while DuckDB has Ad-hoc analytics, data science, ETL pipelines.

claimreview
type: ClaimReview
is accessible for free: true
conditions of access: Free
claim reviewed: Pinot vs DuckDB
review body: Pinot is a distributed OLAP database designed for real-time analytics at scale across multiple servers, while DuckDB is an embedded SQL database optimized for fast in-process analytics on single machines. Pinot excels with massive datasets and continuous ingestion; DuckDB prioritizes simplicity and query speed on local data.
review rating: Rating
  rating: 5
  worst rating: 1
  best rating: 5
  alternate name: Verified Comparison
author: A Versus B
item reviewed: Pinot vs DuckDB

Concurrent User Support
type: PropertyValue
value: Apache Pinot: 100-500 typical | DuckDB: N/A

Query Latency (Average)
type: PropertyValue
value: Apache Pinot: <100ms | DuckDB: N/A

Data Freshness
type: PropertyValue
value: Apache Pinot: Sub-second to 1 minute | DuckDB: N/A

License Type
type: PropertyValue
value: Apache Pinot: Apache 2.0 Open Source | DuckDB: N/A

Deployment Flexibility
type: PropertyValue
value: Apache Pinot: Kubernetes, on-premises, all cloud providers | DuckDB: N/A

Ingestion Streaming Support
type: PropertyValue
value: Apache Pinot: 1M+ eps native | DuckDB: N/A

Base Monthly Cost (Small Cluster)
type: PropertyValue
value: Apache Pinot: Self-hosted infrastructure costs (highly variable) | DuckDB: N/A

Query Latency (Median)
type: PropertyValue
value: Apache Pinot: <100 ms | DuckDB: N/A

Streaming Ingestion Latency
type: PropertyValue
value: Apache Pinot: <1 second | DuckDB: N/A

On-Demand Query Pricing
type: PropertyValue
value: Apache Pinot: Free (self-hosted) / $0.10-0.50 (managed) | DuckDB: N/A

Infrastructure Management
type: PropertyValue
value: Apache Pinot: Manual cluster management required | DuckDB: N/A

Maximum Daily Event Throughput
type: PropertyValue
value: Apache Pinot: 10+ billion events/day (proven at LinkedIn, Airbnb) | DuckDB: N/A

Time to Deploy
type: PropertyValue
value: Apache Pinot: 40-80 hours (cluster provisioning, tuning) | DuckDB: N/A

Concurrent Users Supported
type: PropertyValue
value: Apache Pinot: 100-500 (depends on cluster config) | DuckDB: N/A

Ingestion Rate (events/second)
type: PropertyValue
value: Apache Pinot: 1,000,000+ | DuckDB: 50,000
value reference: Apache Pinot

Query Latency (1B rows)
type: PropertyValue
value: Apache Pinot: 2-5 | DuckDB: 0.5-2
value reference: DuckDB

Maximum Recommended Dataset Size
type: PropertyValue
value: Apache Pinot: 10,000+ | DuckDB: 1
value reference: Apache Pinot

Deployment Time
type: PropertyValue
value: Apache Pinot: 6 | DuckDB: 0.08
value reference: DuckDB

Minimum Cluster Size
type: PropertyValue
value: Apache Pinot: 3-5 | DuckDB: 1
value reference: DuckDB

Memory Per Node
type: PropertyValue
value: Apache Pinot: 50-200 | DuckDB: 2-64 (varies)
value reference: DuckDB

Multi-node Support
type: PropertyValue
value: Apache Pinot: Yes (native distributed) | DuckDB: No (single-node only)

Real-time Upsert Support
type: PropertyValue
value: Apache Pinot: Yes | DuckDB: No (batch only)

Query Latency (1GB aggregation)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 10-50ms

Compression Ratio (typical)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 4:1 to 8:1

Memory Required (minimal)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 10-50MB

Ingest Throughput
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 10-50 million rows/sec

GitHub Stars (2026)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 18,500+

Aggregation Query Time (1 billion rows)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 0.5-2 seconds

Memory Usage (1TB analytical dataset)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 10-50 GB

ACID Compliance Level
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: Partial (batch insert-optimized)

Concurrent Write Support
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: Single-threaded writes only

Years in Production
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 5 years (since 2019)

Native Format Support
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: Parquet, CSV, JSON, Iceberg, Hugging Face

Database File Size Limit
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: Unlimited

Production Deployments (estimated)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: Growing (100K+)

Typical Maximum Dataset Size
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: ~100 GB

Query Latency (100M rows, simple aggregation)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 50-200ms

Idle Memory Usage
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 50-100 MB

Supported Data Formats
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 12+ formats

Typical Query Latency (1GB dataset)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 50-200ms

Maximum Practical Data Size
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 256GB

Memory Required Per Query
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 10-50MB

Setup Time for Basic Analytics
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 1-5 minutes

Primary Language Support
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: Python, SQL, C++, R, Julia, Node.js

Query Latency (1GB CSV)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 150-500ms

Minimum Memory Requirement
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 0.1-0.5 GB

Setup Time (from scratch)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 2-5 (local install)

Multi-machine Distributed Computing
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: Not supported

Fault Tolerance
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: No (single machine)

Aggregation Query Speed (10M rows)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 2.3s

Memory Usage (1GB dataset)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 450MB

SQL Standard Coverage
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 95%

ACID Transactions
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: Fully supported

Core Language
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: C++ (Rust bindings available)

Language Bindings Supported
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 5 (Python, R, Java, Node.js, Go)

Latest Stable Version
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: v0.10.0 (2024)

Total Cost of Ownership (Annual, 100TB dataset)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: $0

Setup Time to First Query
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: < 1 minute

Query Latency (10GB dataset, simple aggregate)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 0.3 seconds

Query Latency (1TB dataset, complex join)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 3-5 seconds

Maximum Supported Dataset Size
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 2 TB (local)

Concurrent User Queries
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 1-5 simultaneous

Built-in Machine Learning Capabilities
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: No (requires external integration)

GitHub Stars (Community Traction)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 18,500+

Query Performance on 10GB Parquet File (GROUP BY aggregation)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 1.2 seconds

Memory Usage (10GB dataset analysis)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 2.1 GB (with compression)

Startup/Import Time
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 45ms (lightweight binary)

Number of Built-in Data Transformation Methods
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 65 SQL functions + standard

Stack Overflow Questions (as of 2026)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 8.2K questions

Maximum Dataset Size (without disk streaming)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 1000+ GB (out-of-core)

SQL Window Function Support
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: Yes (ROW_NUMBER, LAG, LEAD, RANK, etc.)

Time to Analyze 100MB CSV (end-to-end)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 3.8 seconds

Base Monthly Cost
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: Free

Free Tier Storage
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: Unlimited (disk-dependent)

Free Tier Row Reads/Month
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: Unlimited

Global Edge Locations
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: None (local only)

OLAP Query Speed (1GB dataset)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 50-100ms

Replication Latency
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: Not supported

Supported Languages
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 7 (Python, Node.js, Go, Rust, R, Java, C++)

Installation Required
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: No (embedded library)

Query Speed (1GB CSV aggregation)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 1.2 seconds

Maximum Practical Dataset Size
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 100+ GB

Memory Usage (1GB CSV load)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 200 MB (compressed)

Built-in Statistical Functions
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 200+

SQL Support Level
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: Full ANSI SQL + extensions

Learning Curve (1-10 scale)
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 7 (requires SQL)

Stack Overflow Questions Answered
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 3,200

First Release Year
type: PropertyValue
value: Apache Pinot: N/A | DuckDB: 2019

SpeakableSpecification
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Apache Pinot — Wikipedia
type: CreativeWork

DuckDB — Wikipedia
type: CreativeWork

Compare Apache Pinot vs DuckDB
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additional type: CompareAction
target: https://www.aversusb.net/compare/pinot-vs-duckdb)
object: Apache Pinot
object: DuckDB

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

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: Complexity

Minimum Cluster Size
type: PropertyValue
value reference: Infrastructure

Memory Per Node
type: PropertyValue
value reference: Infrastructure

Multi-node Support
type: PropertyValue
value reference: Architecture

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

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

Compression Ratio (typical)
type: PropertyValue
value reference: Efficiency

Memory Required (minimal)
type: PropertyValue
value reference: Resource Usage

Ingest Throughput
type: PropertyValue
value reference: Performance

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

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

Memory Usage (1TB analytical dataset)
type: PropertyValue
value reference: Resource Efficiency

ACID Compliance Level
type: PropertyValue
value reference: Reliability

Concurrent Write Support
type: PropertyValue
value reference: Concurrency

Years in Production
type: PropertyValue
value reference: Maturity

Native Format Support
type: PropertyValue
value reference: Features

Database File Size Limit
type: PropertyValue
value reference: Scalability

Production Deployments (estimated)
type: PropertyValue
value reference: Adoption

Typical Maximum Dataset Size
type: PropertyValue
value reference: Scalability

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

Idle Memory Usage
type: PropertyValue
value reference: Resource Efficiency

Supported Data Formats
type: PropertyValue
value reference: Compatibility

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

Maximum Practical Data Size
type: PropertyValue
value reference: Scalability

Memory Required Per Query
type: PropertyValue
value reference: Resource Efficiency

Setup Time for Basic Analytics
type: PropertyValue
value reference: Ease of Use

Primary Language Support
type: PropertyValue
value reference: Developer Experience

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

Minimum Memory Requirement
type: PropertyValue
value reference: Performance

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

Multi-machine Distributed Computing
type: PropertyValue
value reference: Architecture

Fault Tolerance
type: PropertyValue
value reference: Reliability

Aggregation Query Speed (10M rows)
type: PropertyValue
value reference: Performance

Memory Usage (1GB dataset)
type: PropertyValue
value reference: Resource Efficiency

SQL Standard Coverage
type: PropertyValue
value reference: Feature Completeness

ACID Transactions
type: PropertyValue
value reference: Data Integrity

Core Language
type: PropertyValue
value reference: Implementation

Language Bindings Supported
type: PropertyValue
value reference: Ecosystem

Latest Stable Version
type: PropertyValue
value reference: Maturity

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

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

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

Query Performance on 10GB Parquet File (GROUP BY aggregation)
type: PropertyValue
value reference: Performance

Memory Usage (10GB dataset analysis)
type: PropertyValue
value reference: Resource Efficiency

Startup/Import Time
type: PropertyValue
value reference: Performance

Number of Built-in Data Transformation Methods
type: PropertyValue
value reference: API Completeness

Stack Overflow Questions (as of 2026)
type: PropertyValue
value reference: Community Support

Maximum Dataset Size (without disk streaming)
type: PropertyValue
value reference: Scalability

SQL Window Function Support
type: PropertyValue
value reference: SQL Features

Time to Analyze 100MB CSV (end-to-end)
type: PropertyValue
value reference: Workflow Speed

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: Global Presence

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

Replication Latency
type: PropertyValue
value reference: Performance

Supported Languages
type: PropertyValue
value reference: Accessibility

Installation Required
type: PropertyValue
value reference: Convenience

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