Best of DuckDB2025

  1. 1
    Article
    Avatar of duckdbDuckDB·1y

    The DuckDB Local UI

    DuckDB, in collaboration with MotherDuck, has introduced a built-in local UI available starting from DuckDB v1.2.1. This UI can be launched via terminal or a SQL command and offers features such as interactive notebooks, a column explorer, and detailed table summaries. It runs all queries locally, ensuring data privacy unless explicitly connected to MotherDuck. The UI is designed to be simple, fast, feature-rich, and fully open source.

  2. 2
    Article
    Avatar of duckdbDuckDB·44w

    DuckLake 0.2

    DuckLake 0.2 introduces significant improvements including secrets management for credentials, enhanced Parquet file settings, relative schema/table paths for better organization, name mapping for existing Parquet files, scoped settings at schema and table levels, and partition transforms. The update includes automatic migration from v0.1 and adds new functions like ducklake_list_files for better system integration.

  3. 3
    Article
    Avatar of duckdbDuckDB·34w

    Announcing DuckDB 1.4.0

    DuckDB 1.4.0 'Andium' introduces Long Term Support with 1 year community maintenance, database encryption using AES-256, MERGE statement for upsert operations, Iceberg write support, CLI progress bar with ETA, FILL window function for interpolation, and performance improvements including sorting rework and materialized CTEs. The release also includes macOS notarization and moves Python integration to a separate repository.

  4. 4
    Article
    Avatar of duckdbDuckDB·48w

    Faster Dashboards with Multi-Column Approximate Sorting

    Advanced multi-column sorting techniques using space filling curves (Morton and Hilbert encodings) and truncated timestamps can significantly improve query performance on columnar data formats. These methods enable approximate sorting across multiple columns simultaneously, allowing diverse dashboard queries to benefit from min-max indexes and row group pruning. Experiments on flight data show Hilbert encoding provides the most consistent performance across different query patterns, while sorting by truncated timestamps (year-level granularity) combined with Hilbert encoding works best for time-filtered queries.

  5. 5
    Article
    Avatar of duckdbDuckDB·22w

    Announcing DuckDB 1.4.3 LTS

    DuckDB 1.4.3 LTS is now available with important bugfixes addressing correctness issues in HAVING clauses, JOIN operations, and indexed table updates. The release introduces beta support for Windows ARM64, including native extension distribution and Python wheels via PyPI. Benchmarks on TPC-H SF100 show 24% performance improvement for native ARM64 compared to emulated AMD64 on Snapdragon-based systems. Additional fixes include race condition crashes, memory management improvements during WAL replay, and various edge cases in Unicode handling and Parquet exports.

  6. 6
    Article
    Avatar of duckdbDuckDB·51w

    Announcing DuckDB 1.3.0

    DuckDB version 1.3.0 introduces several new features and improvements, including external file caching, direct query capabilities via the CLI, Python-style lambda syntax, support for UUID v7, expression support in CREATE SECRET, and improved spatial join efficiency. The release also makes internal changes to enhance performance and reliability, particularly for Parquet file handling and string compression.

  7. 7
    Article
    Avatar of duckdbDuckDB·1y

    Preview: Amazon S3 Tables in DuckDB

    DuckDB announces a new preview feature that supports Apache Iceberg REST Catalogs, enabling easy connection to Amazon S3 Tables and Amazon SageMaker Lakehouse. It allows DuckDB users to read and query Iceberg tables directly from these platforms. The guide provides detailed steps for installing necessary extensions from the core_nightly repository and setting up S3 table buckets. The feature is currently experimental and a stable release is expected later in the year.

  8. 8
    Article
    Avatar of duckdbDuckDB·26w

    Announcing DuckDB 1.4.2 LTS

    DuckDB 1.4.2 LTS is now available with critical security fixes for database encryption vulnerabilities, new Iceberg extension support for insert/update/delete operations, enhanced logging and profiling capabilities including HTTP request timing, and Vortex file format support. The release also includes performance optimizations for WAL index operations and database detachment, plus fixes for crashes, incorrect results, and storage issues.