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快速进程内分析引擎

排名更新于 2026年6月30日

For 本地查询 CSV 和 Parquet 的引擎, the strongest matches are cwida/duckdb (DuckDB is an embedded, in-process analytical SQL database that), duckdb/duckdb (DuckDB is an in-process analytical database engine with a) and apache/datafusion (Apache DataFusion is an embedded, columnar SQL query engine). pola-rs/polars and clickhouse/clickhouse round out the shortlist. Each is ranked by relevance to your query, popularity and recent activity.

用于直接针对本地数据文件和数据集执行复杂分析查询的高性能库。

快速进程内分析引擎

用 AI 发现最棒的仓库。我们将通过 AI 为您搜索最匹配的仓库。
  • cwida/duckdbcwida 的头像

    cwida/duckdb

    38,822在 GitHub 上查看↗

    DuckDB is an embedded, in-process analytical SQL database and OLAP database management system. It functions as a data engine for Parquet and CSV files, allowing users to execute complex SQL queries on large datasets without requiring a separate server process. The system is designed for local analytical processing and embedded data science workflows. It enables the direct querying and analysis of Parquet and CSV files from disk, bypassing the need to load data into a permanent database. The engine provides high-performance analytical SQL execution, including support for window functions and

    DuckDB is an embedded, in-process analytical SQL database that natively queries CSV, Parquet, and JSON files with columnar storage and high-performance vectorized execution, exactly matching your need for an in-process analytics engine that works directly on local data files.

    C++In-Process AnalyticsSQL Query Execution EnginesColumnar Databases
    在 GitHub 上查看↗38,822
  • duckdb/duckdbduckdb 的头像

    duckdb/duckdb

    38,805在 GitHub 上查看↗

    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

    DuckDB is an in-process analytical database engine with a SQL interface, columnar storage, and native support for querying local CSV, Parquet, and JSON files, making it a perfect fit for your need to quickly analyze local data files without server overhead.

    C++In-Process AnalyticsSQL EnginesColumnar Engines
    在 GitHub 上查看↗38,805
  • apache/datafusionapache 的头像

    apache/datafusion

    8,908在 GitHub 上查看↗

    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

    Apache DataFusion is an embedded, columnar SQL query engine that runs inside your application without a separate server, supports querying CSV, Parquet, and JSON files, and provides zero-copy access via Apache Arrow—exactly what this search is asking for.

    RustSQL Query Execution EnginesColumnar EnginesSQL Query Execution
    在 GitHub 上查看↗8,908
  • pola-rs/polarspola-rs 的头像

    pola-rs/polars

    38,855在 GitHub 上查看↗

    Polars is a high-performance columnar data processing library designed for efficient analytical workflows. It functions as a structured data library that organizes information into typed columns, utilizing the Apache Arrow memory format to enable zero-copy data sharing and cache-friendly, vectorized operations. The engine is built to handle large-scale tabular datasets, providing both local and distributed analytical runtimes that scale from single-machine environments to multi-node clusters. The project distinguishes itself through a sophisticated lazy query engine that constructs abstract e

    Polars is an in-process columnar analytics engine that uses Apache Arrow for zero-copy data access and natively reads CSV, Parquet, and JSON files while offering a SQL query interface, making it an ideal embedded library for quickly querying local data files.

    RustColumnar Storage EnginesCSV ProcessingParquet Readers
    在 GitHub 上查看↗38,855
  • clickhouse/clickhouseClickHouse 的头像

    ClickHouse/ClickHouse

    48,229在 GitHub 上查看↗

    ClickHouse is a high-performance, columnar analytical database designed for real-time query execution and large-scale data aggregation. It functions as a distributed data warehouse capable of processing petabytes of information, while also providing an embedded engine that integrates directly into applications for native query capabilities without external dependencies. The system is built to handle high-throughput ingestion and complex analytical workloads, delivering millisecond-level latency for interactive dashboards and operational monitoring. The platform distinguishes itself through ad

    ClickHouse is a high-performance columnar analytical database with an embedded engine that runs in-process, supports SQL, and can query local file formats like CSV and Parquet, making it a solid fit for an in-process analytics engine.

    C++Columnar Storage EnginesColumnar DatabasesEmbedded Database Engines
    在 GitHub 上查看↗48,229
  • alasql/alasqlA

    AlaSQL/alasql

    7,278在 GitHub 上查看↗

    AlaSQL is a JavaScript SQL database engine that allows for the filtering, grouping, and joining of in-memory object arrays and JSON data. It functions as an in-memory SQL database and client-side data processor, enabling the execution of SQL statements against JavaScript arrays and external data sources in both browser and server environments. The project serves as a universal data query tool capable of performing relational joins across diverse sources, such as merging Google Spreadsheets, SQLite files, and remote APIs into a single result set. It also acts as an IndexedDB SQL wrapper, allow

    AlaSQL runs in-process as a JavaScript SQL database engine and can query JSON and CSV data, which directly fits your interest in an embedded analytics engine even though it does not use columnar storage or natively support Parquet.

    JavaScriptSQL EnginesSQL Query Execution
    在 GitHub 上查看↗7,278
  • facebookincubator/veloxfacebookincubator 的头像

    facebookincubator/velox

    4,155在 GitHub 上查看↗

    Velox is a high-performance C++ query execution engine and columnar data processing library. It serves as a composable framework for implementing analytical query engines, providing a vectorized expression evaluator and a toolkit for data management systems. The project is distinguished by its use of vectorized columnar execution and arena-based memory allocation to process large-scale datasets. It features specialized optimizations such as broadcast join table caching, dynamic filter push-down, and dictionary encoding to reduce memory overhead and accelerate analytical reads. The engine cov

    Velox is a high-performance columnar execution engine library designed for in-process analytical query processing, supporting file formats like Parquet and JSON through connectors, making it a strong fit as an embedded analytics engine for querying local files, though it requires integration for a full SQL interface.

    C++Columnar Formats
    在 GitHub 上查看↗4,155

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