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4 Repos

Awesome GitHub RepositoriesColumnar Engines

Database architectures optimized for column-based storage and retrieval.

Distinguishing note: Focuses on the storage architecture rather than the query interface.

Explore 4 awesome GitHub repositories matching data & databases · Columnar Engines. Refine with filters or upvote what's useful.

Awesome Columnar Engines GitHub Repositories

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  • duckdb/duckdbAvatar von duckdb

    duckdb/duckdb

    38,805Auf GitHub ansehen↗

    DuckDB is an in-process analytical database engine designed to run directly within an application process. As a zero-dependency, embedded system, it provides enterprise-grade SQL data processing capabilities without the overhead of managing a dedicated database server. It is built to handle complex analytical and aggregation tasks by storing and retrieving information in columns, allowing for high-performance relational data manipulation. The engine distinguishes itself through a columnar vectorized execution model that maximizes CPU cache efficiency during query operations. It employs adapti

    Stores and retrieves information in columns to optimize performance for complex analytical tasks.

    C++analyticsdatabaseembedded-database
    Auf GitHub ansehen↗38,805
  • apache/datafusionAvatar von apache

    apache/datafusion

    8,908Auf GitHub ansehen↗

    Apache DataFusion is an extensible, columnar SQL query engine that runs embedded within a host application without requiring a separate server process. It processes data in columnar batches using Apache Arrow for memory-efficient analytics, and can scale analytic workloads across multiple nodes for parallel execution. The engine supports both SQL and DataFrame queries through a modular, streaming architecture that allows custom operators, data sources, functions, and optimizer rules. The engine distinguishes itself through its modular extension framework, which enables building custom query e

    Processes data in columnar batches using Apache Arrow for memory-efficient analytics.

    Rustarrowbig-datadataframe
    Auf GitHub ansehen↗8,908
  • tconbeer/harlequinAvatar von tconbeer

    tconbeer/harlequin

    6,165Auf GitHub ansehen↗

    Harlequin is a terminal-based SQL IDE that runs queries against DuckDB and SQLite databases, with a plug-in adapter system for connecting to additional database engines. It provides a full-screen text editor with syntax highlighting and fuzzy autocomplete for writing SQL, and displays query results in a scrollable table within the terminal. The application distinguishes itself through a tree-based data catalog that lets you browse database schemas, local files, and remote S3 objects, with the ability to insert or copy paths directly into the query editor. It supports custom key bindings throu

    Opens DuckDB sessions by default, creating database files if they do not exist.

    Python
    Auf GitHub ansehen↗6,165
  • alibaba/alisqlAvatar von alibaba

    alibaba/AliSQL

    5,706Auf GitHub ansehen↗

    AliSQL is a fork of MySQL by Alibaba that extends the relational database management system with enhancements for high performance, scalability, and enterprise-grade availability. It retains the core MySQL identity as a SQL-based database for storing, organizing, and retrieving structured data, while adding optimizations for large-scale transactional and analytical workloads. The project differentiates itself through a set of Alibaba-specific improvements, including a columnar engine for accelerating analytical queries directly on MySQL tables, and a distributed, shared-nothing NDB Cluster en

    Executes analytical SQL queries directly against MySQL tables using an embedded DuckDB columnar engine.

    C++alisqldatabaseduckdb
    Auf GitHub ansehen↗5,706
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  3. Columnar Engines

Unter-Tags erkunden

  • DuckDB-Powered Engines1 Sub-TagColumnar engines that use DuckDB to execute analytical SQL queries directly against MySQL tables. **Distinct from Columnar Engines:** Distinct from Columnar Engines: specifically uses DuckDB as the embedded engine, not a custom columnar format.