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duckdb-test-staging

https://github.com/duckdb/duckdb-test-staging

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (16.7%) to scientific vocabulary
Last synced: 7 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: duckdb
  • License: mit
  • Language: C++
  • Default Branch: main
  • Size: 277 MB
Statistics
  • Stars: 1
  • Watchers: 2
  • Forks: 2
  • Open Issues: 1
  • Releases: 0
Created about 2 years ago · Last pushed over 1 year ago
Metadata Files
Readme Contributing License Code of conduct Citation

README.md

DuckDB logo


Github Actions Badge discord Latest Release

DuckDB

DuckDB is a high-performance analytical database system. It is designed to be fast, reliable, portable, and easy to use. DuckDB provides a rich SQL dialect, with support far beyond basic SQL. DuckDB supports arbitrary and nested correlated subqueries, window functions, collations, complex types (arrays, structs, maps), and several extensions designed to make SQL easier to use.

DuckDB is available as a standalone CLI application and has clients for Python, R, Java, Wasm, etc., with deep integrations with packages such as pandas and dplyr.

For more information on using DuckDB, please refer to the DuckDB documentation.

Installation

If you want to install DuckDB, please see our installation page for instructions.

Data Import

For CSV files and Parquet files, data import is as simple as referencing the file in the FROM clause:

sql SELECT * FROM 'myfile.csv'; SELECT * FROM 'myfile.parquet';

Refer to our Data Import section for more information.

SQL Reference

The documentation contains a SQL introduction and reference.

Development

For development, DuckDB requires CMake, Python3 and a C++11 compliant compiler. Run make in the root directory to compile the sources. For development, use make debug to build a non-optimized debug version. You should run make unit and make allunit to verify that your version works properly after making changes. To test performance, you can run BUILD_BENCHMARK=1 BUILD_TPCH=1 make and then perform several standard benchmarks from the root directory by executing ./build/release/benchmark/benchmark_runner. The details of benchmarks are in our Benchmark Guide.

Please also refer to our Build Guide and Contribution Guide.

Support

See the Support Options page.

Owner

  • Name: DuckDB
  • Login: duckdb
  • Kind: organization
  • Location: Amsterdam, The Netherlands

GitHub Events

Total
  • Watch event: 1
  • Pull request event: 1
  • Fork event: 3
Last Year
  • Watch event: 1
  • Pull request event: 1
  • Fork event: 3

Issues and Pull Requests

Last synced: about 1 year ago

All Time
  • Total issues: 0
  • Total pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 0
  • Total pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
  • szarnyasg (2)
Top Labels
Issue Labels
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Dependencies

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