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    3. DuckDB

    DuckDB

    An in-memory, open-source, and free analytical database that speaks SQL, heavily based on vectorization. It can store and process vector embeddings using Array and List data types to enable vector search, bridging the gap between data engineering and AI workflows with fast response times.

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    Websiteduckdb.org
    PublishedJul 1, 2025

    Categories

    1 Item
    Multi Model & Hybrid Databases

    Tags

    4 Items
    #In Memory#Open Source#Analytics#Sql

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    DuckDB is a fast, in-memory, open-source, and free analytical database system that speaks SQL. It is heavily based on vectorization and can store and process vector embeddings using Array and List data types to enable vector search, bridging the gap between data engineering and AI workflows with fast response times. It allows users to query and transform data anywhere using its feature-rich SQL dialect.

    Features

    • Simple: Easy to install and deploy with zero external dependencies, running in-process or as a single binary.
    • Portable: Runs on Linux, macOS, Windows, Android, iOS, and all popular hardware architectures, offering idiomatic client APIs for major programming languages.
    • Feature-rich SQL Dialect: Provides a comprehensive SQL dialect capable of reading and writing file formats such as CSV, Parquet, and JSON, from local file systems and remote endpoints like S3 buckets.
    • Fast Performance: Delivers blazing speed for analytical queries thanks to its columnar engine, which supports parallel execution and can process larger-than-memory workloads.
    • Extensible: Supports third-party features including new data types, functions, file formats, and SQL syntax, with user contributions available as community extensions.
    • Free and Open-Source: Available under the permissive MIT License, with its intellectual property held by the DuckDB Foundation.

    Installation

    DuckDB is seamlessly integrated with major programming languages and can be installed rapidly, often in less than 10 seconds. Supported installation methods include:

    • Shell (via curl)
    • Python (pip)
    • R (install.packages)
    • Java (Maven/JDBC)
    • Node.js (npm)
    • Rust (cargo)
    • Go (go get)