DuckDB is an in-process
SQL OLAP database management system
Why DuckDB?
Simple
- In-process, serverless
- C++11, no dependencies, single file build
- APIs for Python/R/Java/…
All the benefits of a database, none of the hassle.
Installation
Choose your environment to use for DuckDB
- Python
- R
- Java
- node.js
- Julia
- C++
- CLI
- ODBC
Latest release: DuckDB 0.5.1 System detected: Other Installations
pip install duckdb==0.5.1
install.packages("duckdb")
<dependency>
<groupId>org.duckdb</groupId>
<artifactId>duckdb_jdbc</artifactId>
<version>0.5.1</version>
</dependency>
More Options
npm install duckdb
using Pkg
Pkg.add("DuckDB")https://github.com/
https://github.com/
https://github.com/
https://github.com
https://github.com
https://github.com
https://github.com/
https://github.com/
When to use DuckDB
- Processing and storing tabular datasets, e.g. from CSV or Parquet files
- Interactive data analysis, e.g. Joining & aggregate multiple large tables
- Concurrent large changes, to multiple large tables, e.g. appending rows, adding/removing/updating columns
- Large result set transfer to client
When to not use DuckDB
- High-volume transactional use cases (e.g. tracking orders in a webshop)
- Large client/server installations for centralized enterprise data warehousing
- Writing to a single database from multiple concurrent processes
Blog
ArchiveQuerying Postgres Tables Directly From DuckDB
TLDR: DuckDB can now directly query queries stored in PostgreSQL and speed up complex analytical queries without duplicating data. Introduction PostgreSQL is the world’s most advanced open source database (self-proclaimed). From its interesting beginnings as an academic DBMS, it has evolved over the past 30 years into a fundamental workhorse […]
continue readingPersistent Storage of Adaptive Radix Trees in DuckDB
TLDR: DuckDB uses Adaptive Radix Tree (ART) Indexes to enforce constraints and to speed up query filters. Up to this point, indexes were not persisted, causing issues like loss of indexing information and high reload times for tables with data constraints. We now persist ART Indexes to disk, drastically diminishing […]
continue readingRange Joins in DuckDB
TL;DR: DuckDB has fully parallelised range joins that can efficiently join millions of range predicates. Range intersection joins are an important operation in areas such as temporal analytics, and occur when two inequality conditions are present in a join predicate. Database implementations often rely on slow O(N^2) algorithms that compare […]
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