47 dépôts
Tools that analyze database logs and execution statistics to identify bottlenecks and optimize query efficiency.
Distinguishing note: Focuses specifically on database query analysis and execution metrics rather than general system-wide infrastructure monitoring.
Explore 47 awesome GitHub repositories matching data & databases · Query Performance Monitors. Refine with filters or upvote what's useful.
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
Tracks query execution statistics and resource consumption to identify and optimize long-running database operations.
BCC is an eBPF development toolkit and tracing framework used for monitoring and analyzing the Linux kernel. It functions as a performance analysis tool and debugging utility to capture system events, measure kernel latency, and provide network observability. The project distinguishes itself by providing a build system that integrates with LLVM to compile C-like code into BPF bytecode at runtime. It utilizes BPF Type Format data for relocations to maintain cross-kernel compatibility and extracts kernel headers to ensure the generated programs match the specific kernel version. The toolkit co
Produces histograms of execution times for database queries to identify performance bottlenecks.
Vitess is a database clustering system for horizontal scaling of MySQL. It functions as a middleware layer that abstracts complex sharding and physical topology, allowing applications to interact with a distributed database environment through a unified interface. By intercepting and routing SQL queries across multiple shards, it enables large-scale data management while maintaining the appearance of a single database instance. The platform distinguishes itself through its ability to perform online schema migrations and distributed transaction coordination without requiring application downti
Inspects SQL execution plans and statement behavior to optimize database performance and identify bottlenecks in distributed environments.
Knex is a multi-dialect database client that provides a programmatic SQL query builder, a connection pool manager, and a versioned schema migration tool. It enables programmatic database interaction across multiple SQL engines, including PostgreSQL, MySQL, SQLite3, SQL Server, CockroachDB, and Oracle. The project distinguishes itself through a fluent interface for constructing complex SQL statements and a dedicated framework for database seeding. It utilizes specialized dialects to translate generic query representations into database-specific syntax while maintaining a consistent API across
Allows adding comments to generated SQL statements to link executions back to application source code.
Laravel Debugbar is a web-based debugging toolbar and application profiler for Laravel. It provides a visual interface to inspect database queries, logs, and performance metrics in real time to identify and resolve bugs during development. The tool features a database query monitor to capture SQL statements and timings, as well as a request inspector for analyzing route metadata, loaded views, and HTTP request data. It includes a profiler for measuring execution time and memory usage to identify bottlenecks in the request lifecycle. Its observability capabilities cover exception capture, app
Ships a visual logger that analyzes database execution statistics to optimize query efficiency.
Dapper is a lightweight object-relational mapper for .NET that functions as a high-performance data access library. It operates by extending standard database connection interfaces, allowing developers to execute raw SQL queries while automating the mapping of database results to strongly-typed objects. The library distinguishes itself through its use of runtime code generation, which creates high-performance instructions to map database rows to object properties with minimal overhead. It provides flexible data retrieval options, supporting both memory-buffered loading for speed and row-by-ro
Tracks execution time of database commands to identify performance bottlenecks.
git-extras is a collection of command line utilities that extend the functionality of the Git version control system. It provides a suite of shortcuts and additional commands for history manipulation, remote management, repository analysis, and workflow automation. The project distinguishes itself by offering deep integration with hosting providers to manage pull requests and forks, alongside advanced history tools for obliterating sensitive files and rewriting author metadata. It also includes a specialized interactive shell that allows users to execute commands without repeating the binary
Generates a summary report displaying commit counts and full repository paths.
MyBatis-Plus is a persistence framework extension for Java that simplifies data access by reducing boilerplate code. It provides a toolkit for automating common database operations, utilizing dynamic query wrappers and a system for automated CRUD generation. The project distinguishes itself through a code generation system that produces mapper, model, service, and controller layers based on database metadata. It also implements a security layer that prevents SQL injection through input sanitization and blocks dangerous global update or delete operations to prevent accidental data loss. The f
Includes tools to output executed SQL statements and their processing times to identify and resolve slow queries.
bgfx is a cross-platform, graphics rendering abstraction layer designed for high-performance applications. It provides a unified interface that maps high-level rendering commands to native graphics APIs, allowing developers to maintain a single codebase that executes consistently across diverse operating systems and hardware architectures. The library distinguishes itself through a multi-threaded command submission model that decouples rendering logic from the main application thread, effectively minimizing CPU bottlenecks. It utilizes a backend-agnostic command buffer and a deferred resource
Determines geometry visibility using depth tests to avoid unnecessary rendering.
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
Visualizes query performance metrics and execution plans to help identify bottlenecks.
Pinpoint is a distributed application performance management tool designed to trace requests and monitor metrics across large-scale distributed architectures. It functions as a request tracer, topology mapper, and JVM application monitor, providing a backend capable of collecting and visualizing trace data from OpenTelemetry compatible sources. The system distinguishes itself through a combination of bytecode-based instrumentation via a Java agent and topology-based visualization that renders live maps of service interconnections. It captures execution flow across asynchronous boundaries, suc
Analyzes MyBatis database logs and execution statistics to identify query bottlenecks.
Dask est un framework de calcul parallèle et un planificateur de tâches distribué conçu pour mettre à l'échelle les flux de travail de science des données Python, des machines uniques aux grands clusters. Il fonctionne comme un gestionnaire de ressources de cluster qui orchestre la logique computationnelle en représentant les tâches et leurs dépendances sous forme de graphes acycliques dirigés. Cette architecture permet au système d'automatiser la distribution des charges de travail sur le matériel disponible tout en gérant des exigences d'exécution complexes. Le projet se distingue par un moteur d'évaluation paresseuse qui diffère les opérations sur les données jusqu'à ce qu'elles soient explicitement demandées, permettant une optimisation globale du graphe et une allocation efficace des ressources. Il intègre le déversement de données conscient de la mémoire pour éviter les plantages du système lors du traitement de jeux de données dépassant la mémoire disponible, et il utilise la fusion de graphes de tâches pour combiner des séquences d'opérations en étapes d'exécution uniques, minimisant la surcharge de planification et la communication entre nœuds. La plateforme fournit une surface de capacités complète pour l'analyse de données à grande échelle, incluant le support pour l'apprentissage automatique distribué, l'intégration du calcul haute performance et le traitement de données parallèle. Elle offre des outils étendus pour la gestion du cycle de vie des clusters, le profilage des performances et la surveillance en temps réel de l'exécution des tâches. Les utilisateurs peuvent déployer ces environnements sur diverses infrastructures, incluant le matériel local, les fournisseurs cloud, les systèmes conteneurisés et les clusters de calcul haute performance.
Displays planned task execution sequences to identify bottlenecks or memory-intensive patterns in scheduling.
Subfinder is a security reconnaissance framework designed for subdomain enumeration and attack surface management. It functions as a discovery engine that identifies and maps internet-exposed infrastructure, cloud-hosted assets, and network ranges to maintain a comprehensive inventory of an organization's digital footprint. The project distinguishes itself through a modular, template-driven scanning engine that executes security checks against discovered assets. It leverages cloud-native asset discovery to query provider APIs and infrastructure metadata, while supporting distributed agent orc
Provides summary statistics and counts of identified subdomains for target domains.
dbt-core is a command-line framework for transforming data within a warehouse using modular SQL and version control. It functions as a data transformation engine that enables users to define data structures and business logic through declarative configuration files, which the system then compiles into executable code. By managing complex data dependencies through a directed acyclic graph, it ensures that transformation tasks execute in the correct order while maintaining a manifest-driven state to track lineage and execution history. The project distinguishes itself through an adapter-based d
Appends metadata to generated SQL statements to improve auditability and performance tracking.
This project is a curated directory of software, libraries, and resources designed to support the management, monitoring, and deployment of PostgreSQL database environments. It functions as a structured index of community-supported tools, providing a centralized location for users to discover utilities that enhance database functionality and reliability. The directory organizes disparate database solutions into a logical hierarchy, covering areas such as graphical interfaces, backup and recovery utilities, and performance monitoring platforms. By categorizing these resources, it assists in th
Identifies diagnostic tools and observability platforms for tracking database performance and query efficiency.
pgweb is a web-based database client and graphical administration tool for PostgreSQL. It provides a browser-based interface for executing SQL queries, inspecting schemas, and managing database objects. The tool includes a read-only mode that prevents destructive operations by blocking specific SQL keywords. It supports secure remote access to private instances through native SSH tunneling and encrypted database connections. The application covers a broad range of management capabilities, including multi-environment session management, database structure inspection, and the export of query r
Examines execution plans and performance metrics to identify and optimize slow SQL operations.
Highlight est une plateforme d'observabilité full-stack et un système de monitoring qui agrège les logs, les erreurs et les traces distribuées pour fournir une vue unifiée de la santé de l'application. Il fonctionne comme un système de traçage distribué, un service de monitoring d'erreurs et un outil de relecture de session. La plateforme est disponible sous forme de stack de monitoring dockerisée pour des déploiements auto-hébergés sur Linux. Elle se distingue en combinant l'observabilité backend avec un système d'enregistrement visuel qui capture les changements du DOM et les requêtes réseau pour rejouer les interactions des utilisateurs. Le système couvre plusieurs domaines de capacités clés, incluant la gestion centralisée des logs avec des propriétés interrogeables, le suivi des erreurs d'application avec intégration de source maps pour la dés-obfuscation des stack traces, et le traçage distribué des requêtes à travers les microservices. Il inclut également le monitoring de base de données via l'exécution de requêtes nommées et l'analyse de requêtes de recherche pour récupérer des métriques de performance. L'installation peut être effectuée via un déploiement de monitoring auto-hébergé utilisant Docker ou via le provisionnement d'infrastructure cloud.
Runs pre-defined SQL queries by name to retrieve database performance and blocking metrics.
Mikro-ORM is a TypeScript-based object-relational mapping system that provides a unified persistence layer for Node.js applications. It translates TypeScript entities into relational or document-based database schemas, supporting a variety of engines including PostgreSQL, MySQL, MariaDB, MS SQL Server, SQLite, and MongoDB. The project implements the data mapper pattern to decouple in-memory domain models from the database persistence layer. It utilizes a unit of work pattern to track entity changes in memory and commit them in a single coordinated database transaction. The library covers com
Includes a logging system to identify slow database queries and optimize interaction patterns.
LanceDB is a vector database and columnar data store designed to function as a versioned dataset manager and vector search engine. It serves as a high-performance backend for indexing and retrieving high-dimensional embeddings, providing the foundation for machine learning data pipelines. The system distinguishes itself through a combination of cloud-native object storage and immutable version tracking, allowing for data time-travel and reproducible AI experiments. It integrates hybrid search capabilities, merging dense vector similarity with BM25 full-text search and SQL-like scalar filters
Returns detailed execution statistics for processed queries to identify performance bottlenecks and optimize efficiency.
PgHero is a performance dashboard and diagnostic tool for PostgreSQL. It provides a web interface for monitoring database metrics, analyzing query performance, and managing active connections across multiple database instances. The project distinguishes itself by recording query and storage statistics over time, enabling historical trend analysis through a time-range slider. It also identifies missing indexes by analyzing query patterns and integrates with cloud provider APIs to retrieve system-level hardware statistics such as CPU and IOPS. The tool's broader capabilities cover process admi
Records query statistics over time in dedicated tables to enable historical trend analysis.