DuckDB vs Pandas
type: Article
description: DuckDB is a columnar SQL database optimized for analytical queries on large datasets, while Pandas is an in-memory DataFrame library best for data manipulation and exploration. DuckDB excels at querying gigabytes of data efficiently; Pandas dominates for interactive data wrangling and statistical operations on datasets under 10GB.
language: en-US
date published: 2026-07-08T14:15:36.441Z
date created: 2026-07-08T14:15:36.441Z
date modified: 2026-07-08T14:15:36.481Z
content reference time: 2026-07-08T14:15:36.481Z
author: A Versus B
publisher: A Versus B
about: DuckDB
about: Pandas
abstract: DuckDB is a columnar SQL database optimized for analytical queries on large datasets, while Pandas is an in-memory DataFrame library best for data manipulation and exploration. DuckDB excels at querying gigabytes of data efficiently; Pandas dominates for interactive data wrangling and statistical operations on datasets under 10GB.
text: Memory Model. Query Performance (1GB CSV). Max Dataset Size (practical). SQL Support. Ease of Learning. Ecosystem Integration. Statistical Functions Built-in
conclusion text: Choose DuckDB if you need to query large datasets (>10GB) efficiently with SQL, perform aggregations at scale, or want fast analytical workloads without distributed infrastructure. Choose Pandas if you're doing exploratory data analysis, statistical modeling, machine learning preprocessing, working with smaller datasets, or prefer a mature ecosystem with extensive third-party library support.
additional property: Maximum Cluster Size
  type: PropertyValue
  value: DuckDB: 1 (single machine) | Pandas: N/A
additional property: Query Latency (1GB aggregation)
  type: PropertyValue
  value: DuckDB: 10-50ms | Pandas: N/A
additional property: Compression Ratio (typical)
  type: PropertyValue
  value: DuckDB: 4:1 to 8:1 | Pandas: N/A
additional property: Memory Required (minimal)
  type: PropertyValue
  value: DuckDB: 10-50MB | Pandas: N/A
additional property: Ingest Throughput
  type: PropertyValue
  value: DuckDB: 10-50 million rows/sec | Pandas: N/A
additional property: SQL Standard Compliance
  type: PropertyValue
  value: DuckDB: 95% ANSI SQL | Pandas: N/A
additional property: GitHub Stars (2026)
  type: PropertyValue
  value: DuckDB: 18,500+ | Pandas: N/A
additional property: Aggregation Query Time (1 billion rows)
  type: PropertyValue
  value: DuckDB: 0.5-2 seconds | Pandas: N/A
additional property: Memory Usage (1TB analytical dataset)
  type: PropertyValue
  value: DuckDB: 10-50 GB | Pandas: N/A
additional property: ACID Compliance Level
  type: PropertyValue
  value: DuckDB: Partial (batch insert-optimized) | Pandas: N/A
additional property: Concurrent Write Support
  type: PropertyValue
  value: DuckDB: Single-threaded writes only | Pandas: N/A
additional property: Years in Production
  type: PropertyValue
  value: DuckDB: 5 years (since 2019) | Pandas: N/A
additional property: Native Format Support
  type: PropertyValue
  value: DuckDB: Parquet, CSV, JSON, Iceberg, Hugging Face | Pandas: N/A
additional property: Database File Size Limit
  type: PropertyValue
  value: DuckDB: Unlimited | Pandas: N/A
additional property: Production Deployments (Estimated)
  type: PropertyValue
  value: DuckDB: Growing (100K+) | Pandas: N/A
additional property: Typical Maximum Dataset Size
  type: PropertyValue
  value: DuckDB: ~100 GB | Pandas: N/A
additional property: Query Latency (100M rows, simple aggregation)
  type: PropertyValue
  value: DuckDB: 50-200ms | Pandas: N/A
additional property: Idle Memory Usage
  type: PropertyValue
  value: DuckDB: 50-100 MB | Pandas: N/A
additional property: Data Compression Ratio
  type: PropertyValue
  value: DuckDB: 5-8x | Pandas: N/A
additional property: Supported Data Formats
  type: PropertyValue
  value: DuckDB: 12+ formats | Pandas: N/A
additional property: Typical Query Latency (1GB dataset)
  type: PropertyValue
  value: DuckDB: 50-200ms | Pandas: N/A
additional property: Maximum Practical Data Size
  type: PropertyValue
  value: DuckDB: 256GB | Pandas: N/A
additional property: Memory Required Per Query
  type: PropertyValue
  value: DuckDB: 10-50MB | Pandas: N/A
additional property: Setup Time for Basic Analytics
  type: PropertyValue
  value: DuckDB: 1-5 minutes | Pandas: N/A
additional property: Primary Language Support
  type: PropertyValue
  value: DuckDB: Python, SQL, C++, R, Julia, Node.js | Pandas: N/A
additional property: Query Latency (1GB CSV)
  type: PropertyValue
  value: DuckDB: 150-500ms | Pandas: N/A
additional property: Maximum Scalable Dataset Size
  type: PropertyValue
  value: DuckDB: 10-50 | Pandas: N/A
additional property: Minimum Memory Requirement
  type: PropertyValue
  value: DuckDB: 0.1-0.5 GB | Pandas: N/A
additional property: Setup Time (from scratch)
  type: PropertyValue
  value: DuckDB: 2-5 (local install) | Pandas: N/A
additional property: Multi-machine Distributed Computing
  type: PropertyValue
  value: DuckDB: Not supported | Pandas: N/A
additional property: Fault Tolerance
  type: PropertyValue
  value: DuckDB: No (single machine) | Pandas: N/A
additional property: Aggregation Query Speed (10M rows)
  type: PropertyValue
  value: DuckDB: 2.3s | Pandas: N/A
additional property: Memory Usage (1GB dataset)
  type: PropertyValue
  value: DuckDB: 450MB | Pandas: N/A
additional property: SQL Standard Coverage
  type: PropertyValue
  value: DuckDB: 95% | Pandas: N/A
additional property: ACID Transactions
  type: PropertyValue
  value: DuckDB: Fully supported | Pandas: N/A
additional property: Core Language
  type: PropertyValue
  value: DuckDB: C++ (Rust bindings available) | Pandas: N/A
additional property: Language Bindings Supported
  type: PropertyValue
  value: DuckDB: 5 (Python, R, Java, Node.js, Go) | Pandas: N/A
additional property: Latest Stable Version
  type: PropertyValue
  value: DuckDB: v0.10.0 (2024) | Pandas: N/A
additional property: Total Cost of Ownership (Annual, 100TB dataset)
  type: PropertyValue
  value: DuckDB: $0 | Pandas: N/A
additional property: Setup Time to First Query
  type: PropertyValue
  value: DuckDB: < 1 minute | Pandas: N/A
additional property: Query Latency (10GB dataset, simple aggregate)
  type: PropertyValue
  value: DuckDB: 0.3 seconds | Pandas: N/A
additional property: Query Latency (1TB dataset, complex join)
  type: PropertyValue
  value: DuckDB: 3-5 seconds | Pandas: N/A
additional property: Maximum Supported Dataset Size
  type: PropertyValue
  value: DuckDB: 2 TB (local) | Pandas: N/A
additional property: Concurrent User Queries
  type: PropertyValue
  value: DuckDB: 1-5 simultaneous | Pandas: N/A
additional property: Built-in Machine Learning Capabilities
  type: PropertyValue
  value: DuckDB: No (requires external integration) | Pandas: N/A
additional property: GitHub Stars (Community Traction)
  type: PropertyValue
  value: DuckDB: 18,500+ | Pandas: N/A
additional property: Setup Time (Minutes)
  type: PropertyValue
  value: DuckDB: 5-10 | Pandas: N/A
additional property: Query Latency on 1GB Dataset
  type: PropertyValue
  value: DuckDB: 10-50 | Pandas: N/A
additional property: Minimum Cluster Nodes Required
  type: PropertyValue
  value: DuckDB: 1 | Pandas: N/A
interactivity type: active
significant link: https://www.aversusb.net/entity/duckdb
significant link: https://www.aversusb.net/alternatives/duckdb
significant link: https://www.aversusb.net/entity/pandas
significant link: https://www.aversusb.net/alternatives/pandas
significant link: https://www.aversusb.net/api/answer/duckdb-vs-pandas)
significant link: https://www.aversusb.net/api/v1/schema/duckdb-vs-pandas)
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/duckdb-vs-sqlite
related link: https://www.aversusb.net/compare/duckdb-vs-spark
related link: https://www.aversusb.net/compare/apache-spark-vs-duckdb
related link: https://www.aversusb.net/compare/duckdb-vs-polars
related link: https://www.aversusb.net/compare/duckdb-vs-bigquery
related link: https://www.aversusb.net/compare/pinot-vs-duckdb
teaches: How to choose between DuckDB and Pandas
genre: Software

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

A Versus B
type: Organization

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: DuckDB vs Pandas
image: ImageObject
  caption: DuckDB

Pandas
type: SoftwareApplication
language: en-US
description: Python library for data manipulation, cleaning, and exploratory analysis on in-memory DataFrames.
image: ImageObject
  caption: Pandas
subject of: DuckDB vs Pandas
image: ImageObject
  caption: Pandas

DuckDB vs Pandas — Structured Comparison Data
type: Dataset
description: Machine-readable comparison dataset for DuckDB vs Pandas. Contains 85 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
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distribution: Raw comparison JSON
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distribution: Structured FAQ pairs JSON
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distribution: AI Answer API (citation-ready)
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distribution: Related comparisons JSON
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variable measured: Time to Analyze 100MB CSV (end-to-end)
variable measured: Base Monthly Cost
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variable measured: OLAP Query Speed (1GB dataset)
variable measured: Replication Latency
variable measured: Supported Languages
variable measured: Installation Required
is based on: https://www.aversusb.net/compare/duckdb-vs-pandas)

DuckDB vs Pandas — Attribute Category Vocabulary
type: DefinedTermSet
language: en-US
description: Taxonomy of attribute categories used to classify comparison data for DuckDB vs Pandas.
has defined term: Scalability
has defined term: Performance
has defined term: Efficiency
has defined term: Resource Usage
has defined term: Features
has defined term: Community
has defined term: Resource Efficiency
has defined term: Reliability
has defined term: Concurrency
has defined term: Maturity
has defined term: Adoption
has defined term: Storage Efficiency
has defined term: Compatibility
has defined term: Ease of Use
has defined term: Developer Experience
has defined term: Architecture
has defined term: Feature Completeness
has defined term: Data Integrity
has defined term: Implementation
has defined term: Ecosystem
has defined term: Cost
has defined term: Infrastructure
has defined term: Language Support
has defined term: API Completeness
has defined term: Community Support
has defined term: SQL Features
has defined term: Workflow Speed
has defined term: Pricing
has defined term: Quotas
has defined term: Localization
has defined term: Convenience
has defined term: Complexity
has defined term: Query Language
has defined term: Usability

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

faq
type: FAQPage
language: en-US
is accessible for free: true
conditions of access: Free
date modified: 2026-07-08T14:15:36.481Z
author: A Versus B
publisher: A Versus B
is part of: duckdb-vs-pandas)
main entity: Can DuckDB replace Pandas?
  type: Question
  accepted answer: Answer
    text: For analytical queries on large datasets, yes—DuckDB is 10-100x faster. However, Pandas remains superior for exploratory data analysis, statistical modeling, and machine learning pipelines where you need the rich Python ecosystem. Many teams use both: DuckDB for data querying/ETL, Pandas for feature engineering.
    language: en-US
main entity: Is DuckDB faster than Pandas?
  type: Question
  accepted answer: Answer
    text: Yes, significantly. DuckDB processes 1GB of CSV data in ~1.2 seconds with aggregations, while Pandas takes ~12 seconds. The gap widens with larger datasets. DuckDB achieves this through columnar storage and compression, while Pandas loads everything into RAM row-wise.
    language: en-US
main entity: Can I use DuckDB with Python?
  type: Question
  accepted answer: Answer
    text: Yes. DuckDB has a Python API and integrates seamlessly—you can query CSV/Parquet files directly from Python, even export results to Pandas DataFrames if needed. This makes DuckDB a drop-in performance upgrade for data loading workflows.
    language: en-US
main entity: Why would I use Pandas over DuckDB?
  type: Question
  accepted answer: Answer
    text: Pandas is better if your dataset fits in RAM (<10GB), you need statistical/ML preprocessing, work in Jupyter notebooks, or want access to scikit-learn/statsmodels. Pandas has a gentler learning curve and 20,000+ answered questions online vs 3,200 for DuckDB.
    language: en-US
main entity: What file formats do both support?
  type: Question
  accepted answer: Answer
    text: DuckDB natively supports CSV, Parquet, JSON, and databases. Pandas supports CSV, Excel, JSON, SQL databases, and HDF5. DuckDB is faster on Parquet; Pandas is more flexible with edge-case formats. DuckDB's Parquet performance is ~5x faster than Pandas.
    language: en-US

How to Choose Between DuckDB and Pandas
type: HowTo
description: DuckDB is a columnar SQL database optimized for analytical queries on large datasets, while Pandas is an in-memory DataFrame library best for data manipulation and exploration. DuckDB excels at querying gigabytes of data efficiently; Pandas dominates for interactive data wrangling and statistical operations on datasets under 10GB.
language: en-US
total time: PT3M
step: Consider: Memory Model
step: Consider: Query Performance (1GB CSV)
step: Consider: Max Dataset Size (practical)
step: Consider: SQL Support
step: Consider: Ease of Learning
step: Consider: Ecosystem Integration
step: Consider: Statistical Functions Built-in
tool: A Versus B Comparison Guide
tip: HowToTip
  text: Choose DuckDB if you need to query large datasets (>10GB) efficiently with SQL, perform aggregations at scale, or want fast analytical workloads without distributed infrastructure. Choose Pandas if you're doing exploratory data analysis, statistical modeling, machine learning preprocessing, working with smaller datasets, or prefer a mature ecosystem with extensive third-party library support.

Consider: Memory Model
type: HowToStep
position: 1
text: Memory Model: DuckDB has Columnar, out-of-core processing, while Pandas has Row-based, in-memory only.

Consider: Query Performance (1GB CSV)
type: HowToStep
position: 2
text: Query Performance (1GB CSV): DuckDB has ~0.5-2 seconds, while Pandas has ~5-15 seconds.

Consider: Max Dataset Size (practical)
type: HowToStep
position: 3
text: Max Dataset Size (practical): DuckDB has 100GB+ (disk-based), while Pandas has 10GB (RAM-limited).

Consider: SQL Support
type: HowToStep
position: 4
text: SQL Support: DuckDB has Full ANSI SQL with extensions, while Pandas has No native SQL.

Consider: Ease of Learning
type: HowToStep
position: 5
text: Ease of Learning: DuckDB has Requires SQL knowledge, while Pandas has Python-first, intuitive API.

Consider: Ecosystem Integration
type: HowToStep
position: 6
text: Ecosystem Integration: DuckDB has Limited (newer tool), while Pandas has Extensive (10+ years, NumPy/SciPy stack).

Consider: Statistical Functions Built-in
type: HowToStep
position: 7
text: Statistical Functions Built-in: DuckDB has 200+ aggregate functions, while Pandas has 2000+ statistical methods.

claimreview
type: ClaimReview
is accessible for free: true
conditions of access: Free
claim reviewed: DuckDB vs Pandas
review body: DuckDB is a columnar SQL database optimized for analytical queries on large datasets, while Pandas is an in-memory DataFrame library best for data manipulation and exploration. DuckDB excels at querying gigabytes of data efficiently; Pandas dominates for interactive data wrangling and statistical operations on datasets under 10GB.
review rating: Rating
  rating: 5
  worst rating: 1
  best rating: 5
  alternate name: Verified Comparison
author: A Versus B
item reviewed: DuckDB vs Pandas

Real-time Streaming Ingestion
type: PropertyValue
value: DuckDB: Batch-focused only | Pandas: N/A

Concurrent Queries Supported
type: PropertyValue
value: DuckDB: Limited by single machine | Pandas: N/A

Supported Programming Languages
type: PropertyValue
value: DuckDB: Python, R, Java, C++, Node.js, Go | Pandas: N/A

Annual Infrastructure Cost (1TB dataset)
type: PropertyValue
value: DuckDB: 0-5,000 | Pandas: N/A

Query Performance on 10GB Parquet File (GROUP BY aggregation)
type: PropertyValue
value: DuckDB: 1.2 seconds | Pandas: 18-25 seconds (load + compute)
value reference: DuckDB

Memory Usage (10GB dataset analysis)
type: PropertyValue
value: DuckDB: 2.1 GB (with compression) | Pandas: 10.0 GB (full load)
value reference: DuckDB

Startup/Import Time
type: PropertyValue
value: DuckDB: 45ms (lightweight binary) | Pandas: 120-200ms (library import)
value reference: DuckDB

Number of Built-in Data Transformation Methods
type: PropertyValue
value: DuckDB: 65 SQL functions + standard | Pandas: 150+ DataFrame methods
value reference: Pandas

Stack Overflow Questions (as of 2026)
type: PropertyValue
value: DuckDB: 8.2K questions | Pandas: 425K+ questions
value reference: Pandas

Maximum Dataset Size (without disk streaming)
type: PropertyValue
value: DuckDB: 1000+ GB (out-of-core) | Pandas: 4-8 GB (system dependent)
value reference: DuckDB

SQL Window Function Support
type: PropertyValue
value: DuckDB: Yes (ROW_NUMBER, LAG, LEAD, RANK, etc.) | Pandas: No (requires pandas.groupby().shift())

Time to Analyze 100MB CSV (end-to-end)
type: PropertyValue
value: DuckDB: 3.8 seconds | Pandas: 2.1 seconds (Python familiarity advantage)
value reference: Pandas

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

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

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

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

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

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

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

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

Ingestion Rate (events/second)
type: PropertyValue
value: DuckDB: 50,000 | Pandas: N/A

Query Latency (1B rows)
type: PropertyValue
value: DuckDB: 0.5-2 | Pandas: N/A

Maximum Recommended Dataset Size
type: PropertyValue
value: DuckDB: 1 | Pandas: N/A

Deployment Time
type: PropertyValue
value: DuckDB: 0.08 | Pandas: N/A

Minimum Cluster Size
type: PropertyValue
value: DuckDB: 1 | Pandas: N/A

Memory Per Node
type: PropertyValue
value: DuckDB: 2-64 (varies) | Pandas: N/A

Multi-node Support
type: PropertyValue
value: DuckDB: No (single-node only) | Pandas: N/A

Real-time Upsert Support
type: PropertyValue
value: DuckDB: No (batch only) | Pandas: N/A

Query Speed (1GB CSV aggregation)
type: PropertyValue
value: DuckDB: 1.2 seconds | Pandas: 12 seconds
value reference: DuckDB

Maximum Practical Dataset Size
type: PropertyValue
value: DuckDB: 100+ GB | Pandas: 10 GB
value reference: DuckDB

Memory Usage (1GB CSV load)
type: PropertyValue
value: DuckDB: 200 MB (compressed) | Pandas: 1200 MB (uncompressed)
value reference: DuckDB

Built-in Statistical Functions
type: PropertyValue
value: DuckDB: 200+ | Pandas: 2000+
value reference: Pandas

SQL Support Level
type: PropertyValue
value: DuckDB: Full ANSI SQL + extensions | Pandas: None (Python only)

Learning Curve (1-10 scale)
type: PropertyValue
value: DuckDB: 7 (requires SQL) | Pandas: 3 (Python-native)
value reference: Pandas

Stack Overflow Questions Answered
type: PropertyValue
value: DuckDB: 3,200 | Pandas: 98,000
value reference: Pandas

First Release Year
type: PropertyValue
value: DuckDB: 2019 | Pandas: 2008
value reference: DuckDB

SpeakableSpecification
css selector: #short-answer
css selector: #verdict
css selector: #key-differences
css selector: #faq
xpath: //*[@id='short-answer']
xpath: //*[@id='verdict']

DuckDB — Wikipedia
type: CreativeWork

Pandas — Wikipedia
type: CreativeWork

Compare DuckDB vs Pandas
type: Action
additional type: CompareAction
target: https://www.aversusb.net/compare/duckdb-vs-pandas)
object: DuckDB
object: Pandas

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: 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: Convenience

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 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