DuckDB update brings analysis to the edge, now in version 1.2

Joe Green
@TechForge_Media
joe@techforge.pub
“Young Mandarin Duck” by Charles Patrick Ewing is licensed under CC BY 2.0.
DuckDB has announced the release of version 1.2 of its database software, with several feature upgrades and performance improvements.
Code-named Histrionicus (after the magnificent Harlequin duck’s Latin name), version 1.2.0 is the result of over 5,000 commits by more than 70 contributors since version 1.1.3.
Staging a full SQL-compatible database is a fairly trivial task, but many developers need something simpler and lightweight that doesn’t necessarily warrant the full client-server model. The best known solution for a standalone, single database file solution is SQLite, a handy piece of software to be found in literally billions of instances all over the planet.
Produced in the Dutch public sector and later spun off into a full, open-source database technology, DuckDB takes the spirit of simplicity and ease of use that millions of SQLite users love, and adds capabilities that make it the ideal choice for analytics workloads running close to data sources. Edge environments where there’s a need for fast data analysis of IIoT data would be one example, or in places where embedded analytics are required to run on modest hardware.
Where SQLite excels at real-time data processing (transactional workloads), DuckDB is optimised for OLAP workloads (as opposed to OLTP). It users a vectorised, interpreted execution engine, storing fixed-length data types (such as integer values) as native arrays
Like SQLite, it’s designed for use in-process, so ephemeral DBs can be created, queried and dropped as part of larger codebases, and both are ACID compliant (Atomic, Consistent, Isolated, and Durable).
Full release notes are on GitHub and run to over 700 fixes, improvements, new features and tweaks, but some of the highlights include:
DuckDB can process large data sets with limited hardware without compromising on performance. With smaller data sets, it performs as well as its direct analogue, SQLite, but the larger the data set, SQLite can begin to slow because of its row-based execution model.
As with any software choice, it’s a case of horses for courses. The user base for SQLite is vast, and it’s a proven technology. DuckDB is perhaps not as well known, but its use-cases are deliberately different and its design ethos makes it a solution for particular settings and requirements.
Joe Green
@TechForge_Media
joe@techforge.pub
24 February 2025
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