DuckDB 1.0 has been released following a successful release of the 0.10 version back in February that introduced a version of DuckDB with both forward and backward compatibility for DuckDB's storage format. 

DuckDB is a relational database that has already gained popularity with millions of downloads a month. Download traffic for just the DuckDB extensions is running at upwards of four terabytes a day.

The developers describe DuckDB's advantages as simplicity, portability, speed, feature richness, and the fact it's free. They say the simplicity comes from the fact it is easy to install, and has embedded in-process operation. DuckDB has no external dependencies either at compilation or runtime. It doesn't run as a separate process, but is completely embedded within a host process. This ensures high-speed data transfer to and from the database for analytical uses.

The lack of dependencies ensures portability. DuckDB can be compiled for all major operating systems, and will run on machines ranging from small, resource-constrained edge devices to large multi-terabyte memory servers with 100+ CPU cores. Using DuckDB-Wasm, DuckDB can also run in web browsers and even on mobile phones.

DuckDB provides APIs for Java, C, C++, Go, Node.js, Julia, Python, R, Rust, Swift, ODBC and Wasm. DuckDB is deeply integrated into Python and R for efficient interactive data analysis.

In terms of features, DuckDB offers support for complex queries in SQL with a large function library and window functions. It provides transactional guarantees (ACID properties) , and data can be stored in persistent, single-file databases. DuckDB supports secondary indexes to speed up queries trying to find a single table entry.

DuckDB's speed is another attraction. It is designed to support analytical query workloads, which tend to have complex, relatively long-running queries that process significant portions of the stored dataset. To support this, DuckDB contains a columnar-vectorized query execution engine, where queries are still interpreted, but a large batch of values are processed in one operation.

DuckDB also offers a flexible extension mechanism that allows defining new data types, functions, file formats and new SQL syntax. The developers say that many of DuckDB's key features, such as support for the Parquet file format, JSON, time zones, and supports for the HTTP(S) and S3 protocols are implemented as extensions.

DuckDB is open-source, the entire source code is freely available on GitHub. The team is holding its next community event, DuckCon #5, in Seattle on August 15, and attendance is free.

More Information

DuckDB Website

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