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2 Repos

Awesome GitHub RepositoriesIn-Database Columnar Engines

Columnar query engines embedded directly within the database to run analytical SQL workloads on live data.

Distinct from Columnar Analytics: Distinct from Columnar Analytics: focuses on the embedded engine architecture within the database, not general columnar query capabilities.

Explore 2 awesome GitHub repositories matching data & databases · In-Database Columnar Engines. Refine with filters or upvote what's useful.

Awesome In-Database Columnar Engines GitHub Repositories

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  • 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 Arrow columnar batches through a streaming pipeline without materializing intermediate results.

    Rustarrowbig-datadataframe
    Auf GitHub ansehen↗8,908
  • 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

    MySQL executes analytical SQL workloads directly on a columnar storage engine, accelerating aggregation and scan-heavy queries.

    C++alisqldatabaseduckdb
    Auf GitHub ansehen↗5,706
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  4. In-Database Columnar Engines

Unter-Tags erkunden

  • Streaming Columnar ExecutionsProcessing data in Arrow columnar batches through a streaming pipeline without materializing intermediate results. **Distinct from In-Database Columnar Engines:** Distinct from In-Database Columnar Engines: focuses on streaming execution without materialization, not the embedded engine architecture.