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محركات استعلام SQL لملفات البيانات

تم تحديث الترتيب في 30 يونيو 2026

For تشغيل استعلامات SQL مباشرة على ملفات البيانات, the strongest matches are cwida/duckdb (DuckDB is an embedded analytical SQL engine purpose-built for), duckdb/duckdb (DuckDB is an in-process analytical SQL engine that natively) and apache/datafusion (Apache DataFusion is an embedded columnar SQL query engine). harelba/q and cube2222/octosql round out the shortlist. Each is ranked by relevance to your query, popularity and recent activity.

أدوات عالية الأداء تتيح الاستعلام المباشر بلغة SQL عن تنسيقات بيانات CSV و Parquet دون الحاجة إلى استيعابها.

محركات استعلام SQL لملفات البيانات

اعثر على أفضل المستودعات باستخدام الذكاء الاصطناعي.سنبحث عن أفضل المستودعات المطابقة باستخدام الذكاء الاصطناعي.
  • cwida/duckdbالصورة الرمزية لـ cwida

    cwida/duckdb

    38,822عرض على GitHub↗

    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 analytical SQL engine purpose-built for running SQL queries directly on CSV and Parquet files from disk, exactly matching the need for ad-hoc file query with automatic schema inference and columnar execution.

    C++SQL Query Execution EnginesParquet ScannersVectorized Execution Engines
    عرض على GitHub↗38,822
  • duckdb/duckdbالصورة الرمزية لـ duckdb

    duckdb/duckdb

    38,805عرض على GitHub↗

    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 SQL engine that natively queries CSV and Parquet files without any import step, with columnar execution, schema inference, and cloud storage support built in — exactly what this search is after.

    C++SQL Execution InterfacesVectorized Execution Engines
    عرض على GitHub↗38,805
  • apache/datafusionالصورة الرمزية لـ apache

    apache/datafusion

    8,908عرض على GitHub↗

    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 directly queries CSV and Parquet files from local or cloud storage without needing to import them, with full schema inference and columnar execution covering all the features you listed.

    RustSQL Query Execution Engines
    عرض على GitHub↗8,908
  • harelba/qالصورة الرمزية لـ harelba

    harelba/q

    10,353عرض على GitHub↗

    q is a command-line utility for the processing, filtering, and aggregation of tabular text and database files using standard SQL syntax. It functions as a query engine that treats CSV and TSV files, as well as standard input, as relational database tables. The tool distinguishes itself by providing a persistent cache layer that stores processed tabular data in a binary format to accelerate repeated queries on large datasets. It also maps individual filenames or stream identifiers to relational table names, enabling SQL joins across disparate text files. The project covers a broad range of da

    q is a command-line SQL query engine that lets you run standard SQL directly on CSV and TSV files without a database, supporting schema inference and joins—but it does not handle Parquet files, which this search also requires.

    PythonSchema InferenceSQL Query Interfaces
    عرض على GitHub↗10,353
  • cube2222/octosqlالصورة الرمزية لـ cube2222

    cube2222/octosql

    5,258عرض على GitHub↗

    Octosql is a federated SQL query engine, data transformer, and streaming SQL processor. It allows users to execute single SQL statements across multiple disparate data sources, including different database types and file formats, to merge and transform results into a unified set. The system distinguishes itself by treating CSV, JSONLines, and Parquet files as virtual tables and utilizing a plugin-based architecture to extend connectivity to external storage engines. It functions as a streaming processor for infinite data streams, using watermarks, retractions, and tumbling windows to maintain

    Octosql is a federated SQL query engine that treats CSV and Parquet files as virtual tables you can query directly with SQL, fitting your need to run ad-hoc queries without importing into a database.

    GoFile Format QueryingSQL Query Execution Engines
    عرض على GitHub↗5,258
  • wireservice/csvkitالصورة الرمزية لـ wireservice

    wireservice/csvkit

    6,390عرض على GitHub↗

    csvkit is a composable Unix-style command-line toolkit for converting, filtering, and analyzing CSV files directly from the terminal. It provides a suite of focused single-purpose commands that can be combined via pipes to build complex data processing workflows, with a modular architecture that includes a column-type inference engine for automatically detecting data types and a streaming-pipeline design for efficient handling of tabular data. The toolkit distinguishes itself through its SQL-engine abstraction layer, which allows users to run SQL queries directly against CSV files without req

    csvkit is a command-line toolkit that lets you run SQL queries directly on CSV files without importing into a database, but it does not support Parquet files or cloud storage, so it fits the core need with notable gaps.

    PythonCSVCSVCSV
    عرض على GitHub↗6,390
  • trinodb/trinoالصورة الرمزية لـ trinodb

    trinodb/trino

    12,952عرض على GitHub↗

    Trino is a distributed SQL query engine designed for large-scale data analytics. It functions as a data federation platform, providing a unified interface that allows users to execute complex analytical queries across multiple heterogeneous data sources simultaneously without requiring data movement or transformation. The engine utilizes a massively parallel processing architecture to scale compute resources across clusters for high-speed data retrieval. It distinguishes itself through a cost-based query optimizer that analyzes metadata to determine efficient execution plans, alongside dynami

    Trino is a distributed SQL query engine that can run ad-hoc SQL queries directly on CSV and Parquet files (and other formats) from cloud storage or local filesystems without any import step, covering all the features you want—schema inference, columnar execution, and cloud storage support—making it a comprehensive solution for this use case.

    JavaDistributed SQL EnginesFederated Data GatewaysFederated Data Query Engines
    عرض على GitHub↗12,952
  • apache/drillالصورة الرمزية لـ apache

    apache/drill

    2,018عرض على GitHub↗

    Apache Drill is a distributed MPP query layer for self describing data

    Apache Drill is a distributed SQL query engine that directly queries CSV, Parquet, and other file formats without requiring a database, making it an ideal fit for ad-hoc data file analysis.

    JavaAnalytics and SearchDatabases and Storage
    عرض على GitHub↗2,018
  • alasql/alasqlA

    AlaSQL/alasql

    7,278عرض على GitHub↗

    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 is a JavaScript SQL engine that can run queries directly on CSV files and other data sources without a database import, but it lacks explicit support for Parquet files and columnar execution, covering only some of the requested features.

    JavaScriptFile Format QueryingSQL Query Interfaces
    عرض على GitHub↗7,278
  • apache/sparkالصورة الرمزية لـ apache

    apache/spark

    43,467عرض على GitHub↗

    Apache Spark is a unified distributed data processing engine designed for large-scale data analysis and computation graphs. It functions as a distributed machine learning framework, a graph processing system, a real-time stream processor, and a SQL analytics engine. The system enables the execution of distributed SQL querying, large-scale graph analysis, and real-time stream analytics across clusters of machines. It also provides a scalable environment for implementing machine learning algorithms and predictive model development on massive datasets. The engine incorporates relational query e

    Apache Spark is a distributed SQL analytics engine that can query CSV and Parquet files directly without import, covering all requested features including schema inference and cloud storage, but its cluster-oriented design makes it heavier than a typical ad-hoc file query tool.

    ScalaSQL Query Interfaces
    عرض على GitHub↗43,467
قارن بين أفضل 10 في لمحة
المستودعالنجوماللغةالترخيصآخر تحديث
cwida/duckdb38.8KC++MIT17 يونيو 2026
duckdb/duckdb38.8KC++MIT16 يونيو 2026
apache/datafusion8.9KRustApache-2.023 يونيو 2026
harelba/q10.4KPythongpl-3.06 فبراير 2026
cube2222/octosql5.3KGoMPL-2.026 مايو 2024
wireservice/csvkit6.4KPythonMIT18 يونيو 2026
trinodb/trino13KJavaApache-2.023 يونيو 2026
apache/drill2KJavaApache-2.023 يونيو 2026
alasql/alasql7.3KJavaScriptMIT21 يونيو 2026
apache/spark43.5KScalaApache-2.016 يونيو 2026

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