6 مستودعات
Capabilities for querying and importing data from files stored outside the database.
Distinguishing note: Focuses on file-based ingestion rather than internal table management.
Explore 6 awesome GitHub repositories matching data & databases · External Data Access. Refine with filters or upvote what's useful.
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
Provides specialized commands to query and import data directly from structured external files.
Anki is a cross-platform flashcard management system designed to optimize long-term memory retention through spaced-repetition learning. It functions as a digital learning assistant that uses active recall practice and automated scheduling algorithms to determine the ideal timing for card reviews based on individual performance history. The core system relies on a local relational database to ensure data persistence and portability, while supporting complex study workflows through flexible note-type schema modeling and template-driven content rendering. The platform distinguishes itself throu
Loads flashcards and media from text files or packaged deck files to expand study material from external sources.
Locust is a distributed performance testing framework that allows users to define complex system stress scenarios using standard Python code. By modeling concurrent users as classes with weighted tasks and lifecycle hooks, it enables the simulation of realistic user behavior across large-scale environments. The tool functions as a scalable load generator capable of orchestrating traffic across multiple worker nodes to measure system stability and responsiveness under heavy, real-world conditions. The framework is distinguished by its protocol-agnostic architecture, which supports diverse comm
Ingests and distributes external datasets into test scenarios to ensure varied and representative load simulation.
Beekeeper Studio is a cross-platform desktop application designed for database management and SQL development. It provides a unified graphical interface to connect to, query, and modify data across a wide range of relational and NoSQL database systems. The application functions as a comprehensive workspace, integrating tools for schema design, record editing, and data visualization. The project distinguishes itself through a focus on secure, flexible connectivity and AI-assisted workflows. It supports advanced authentication methods, including enterprise single sign-on, multi-factor authentic
Executes SQL commands to read or import data directly from external file formats like CSV, Parquet, and JSON.
Presto is a distributed SQL query engine designed for high-performance analytical processing across heterogeneous data sources. It functions as a data federation platform and massively parallel processing engine, allowing users to execute interactive queries against diverse storage systems without requiring data migration. By mapping remote metadata and structures to a unified relational namespace, it enables seamless cross-platform analysis through a standard SQL interface. The engine distinguishes itself through a pluggable connector architecture and a shared-nothing distributed processing
Accesses diverse storage systems and databases through a pluggable architecture to enable cross-platform data analysis.
CrowdSec is a collaborative, distributed security engine designed for threat detection and infrastructure protection. It functions as an intrusion detection system that parses logs and network traffic to identify malicious patterns, utilizing a bucket-based threshold detection model to aggregate events and trigger alerts. The platform is built on a modular architecture that includes a centralized local API server for managing security signals and a relational database for persistent storage of remediation decisions. What distinguishes the project is its decoupled enforcement model, which offl
Reads structured files into memory to provide reference data for security rules and pattern matching.