7 repositorios
Engines for parsing, validating, and auditing database queries to ensure performance and security.
Distinguishing note: No candidates provided; focuses on query structure analysis rather than execution.
Explore 7 awesome GitHub repositories matching data & databases · SQL Analysis Tools. Refine with filters or upvote what's useful.
p3c is a Java static analysis tool and code quality linter designed to enforce professional coding guidelines and quality standards. It utilizes a set of custom rules based on the PMD engine to scan source code for style violations, performance bottlenecks, and potential bugs. The project is distributed as an IDE linting plugin that provides real-time feedback and warnings during development. It also includes functionality for pre-commit code quality gates, allowing modified files to be scanned and blocked if they violate defined rules before being committed to version control. The analysis
Analyzes SQL query structures to detect inefficient joins, improper index usage, and prohibited pattern matching.
Druid is a database connection management and monitoring framework designed to maintain persistent, high-performance links between applications and relational databases. It functions as a resource manager that automates the lifecycle of connection pools, reducing the overhead associated with repeatedly opening and closing network connections. The project distinguishes itself through an integrated query analysis engine that decomposes database statements into structured components. This capability enables real-time security auditing, syntax validation, and metadata extraction, allowing for the
A programmatic engine that decomposes database queries into structured components to facilitate security auditing, performance monitoring, and syntax validation.
Perspective is a columnar data analytics engine and high-performance visualization component powered by WebAssembly. It provides a system for analyzing and visualizing large or streaming datasets through interactive data grids and charts, utilizing a compiled binary to achieve near-native performance within the browser. The project distinguishes itself through a WebSocket-based data streaming interface and deep Apache Arrow integration, which minimize memory overhead when synchronizing tables between servers and clients. It acts as a remote query proxy capable of translating visualization con
Enables immediate grouping, sorting, filtering, and aggregations on datasets via an interactive viewer.
This project is a plugin framework and agentic workflow library designed to connect large language models to professional toolstacks. It provides a system for integrating language models with external data warehouses, CRMs, and other enterprise software to retrieve and manipulate real-time business data. The framework enables the automation of specialized professional tasks through a file-based plugin definition system. It allows for the customization of domain expertise and plugin behavior to align with internal company processes, supported by an enterprise data connector that links models t
Executes optimized SQL queries across enterprise data warehouses to perform deep dataset analysis.
ThinkStats2 es un curso de estadística computacional y librería educativa diseñada para enseñar probabilidad y estadística a través de un enfoque programático. Proporciona un framework para estudiar conceptos estadísticos escribiendo código Python y ejecutando simulaciones en conjuntos de datos del mundo real. El proyecto utiliza notebooks interactivos y una colección de módulos de Python para impartir lecciones guiadas. Enfatiza la verificación de leyes estadísticas teóricas a través de experimentos computacionales iterativos y pruebas basadas en simulación. El recurso cubre amplias capacidades en análisis de datos y formación en ciencia de datos, permitiendo a los usuarios explorar conjuntos de datos y realizar análisis estadísticos dentro de un entorno programable.
Provides a framework for studying statistical patterns using programmatic analysis of real-world datasets.
Mapshaper es una herramienta para procesar, simplificar y convertir datos vectoriales geográficos, disponible como interfaz de línea de comandos, herramienta de navegador web y librería de Node.js. Funciona como un proyector de coordenadas, convertidor de datos vectoriales y optimizador de activos de mapas web diseñado para transformar conjuntos de datos espaciales entre diferentes sistemas de referencia de coordenadas y formatos de archivo. El proyecto se distingue por su simplificación de geometría que preserva la topología, lo que reduce el número de vértices mientras mantiene los límites compartidos para evitar huecos y superposiciones. Además, optimiza los activos para la web mediante la cuantización de coordenadas y el filtrado de atributos para reducir el tamaño de los archivos. El sistema cubre una amplia gama de capacidades, incluyendo reproyección de coordenadas utilizando cadenas PROJ y códigos EPSG, y conversión de datos entre formatos como Shapefile, GeoJSON, TopoJSON, GeoPackage y KML. Proporciona amplias herramientas de procesamiento de geometría para buffering, recorte, disolución y reparación de topologías, así como utilidades de gestión de datos para unión, filtrado y transformación de atributos. Además, incluye funciones de visualización para generar exportaciones SVG estilizadas, retículas y mapas de símbolos proporcionales. Las capacidades de procesamiento espacial pueden integrarse directamente en aplicaciones JavaScript y tuberías de construcción (build pipelines) a través de su librería de Node.js.
Provides an overview of files by printing geometry types, feature counts, and coordinate systems.
This project is an edge computing development toolkit and serverless command line interface used to develop, test, and deploy serverless functions to a global edge network. It serves as an edge runtime bundler and resource orchestrator, managing the entire lifecycle of edge projects from local development to worldwide distribution. The toolkit distinguishes itself through distributed workflow management, coordinating stateful instances and the durable execution of long-running processes across the edge. It also provides specialized integrations for edge AI, including the management of vector
Allows writing execution data points to datasets for SQL-based observability and performance analysis.