11 repositorios
Techniques and utilities for optimizing database resource usage, query throughput, and system stability during operations.
Distinct from Performance Tuning: The candidates are either too generic, focused on AI, or specifically targeted at connection pools, whereas this is about overall database operational tuning.
Explore 11 awesome GitHub repositories matching data & databases · Database Performance Tuning. Refine with filters or upvote what's useful.
gh-ost is a triggerless online schema migration tool for MySQL. It functions as a replication client and table management utility that synchronizes data from a source table to a shadow table using binary logs, allowing for table structure modifications without locking original tables or causing downtime. The tool distinguishes itself by using binary-log-based replication instead of triggers to stream row-based events to a shadow table. It implements load-aware throttling and dynamic performance tuning to adjust migration speed based on server load and replication lag. Users can monitor and ad
Implements dynamic adjustment of chunk sizes and sleep ratios to balance migration speed with database stability.
MySQLTuner-perl is a diagnostic utility and Perl script designed for optimizing database configurations, auditing security, monitoring resources, and analyzing performance. It functions as a configuration optimizer and performance tuning tool that analyzes server variables to provide specific recommendations for increasing system stability and speed. The tool acts as a database auditor by evaluating security settings, SSL configurations, and schema integrity to identify vulnerabilities. It also serves as a resource monitor that forecasts capacity needs and calculates health scores based on di
Analyzes database configuration variables to provide recommendations that increase speed and system stability.
This project is a comprehensive educational resource and curriculum focused on site reliability engineering, distributed systems, and infrastructure operations. It provides technical guides, a systems engineering course, and instructional manuals designed to teach the principles of managing large-scale computing environments. The curriculum covers high-level architectural design for scalability and resilience, including fault-tolerant infrastructure, high-availability patterns, and microservices decomposition. It emphasizes the practical application of site reliability engineering through the
Teaches techniques for adjusting database server and client parameters to optimize resource usage and stability.
Este proyecto es una guía de entrevistas de ingeniería backend y un recurso de estudio de ciencias de la computación. Proporciona una colección curada de preguntas y respuestas técnicas centradas en arquitectura del lado del servidor, optimización de bases de datos y fundamentos de redes para prepararse para evaluaciones profesionales de ingeniería de software. El recurso funciona como una referencia técnica para estudiar propiedades ACID, aislamiento de transacciones y la optimización de sistemas relacionales y no relacionales. Incluye una referencia de arquitectura de software para analizar patrones de diseño, inyección de dependencias y las compensaciones estructurales de varios frameworks backend. El contenido cubre un amplio rango de dominios técnicos, incluyendo fundamentos de sistemas operativos, estudio de protocolos de red y estructuras de datos. También proporciona un manual para DevOps e infraestructura, detallando pipelines de integración continua, orquestación de contenedores y estrategias de despliegue sin tiempo de inactividad (zero-downtime).
Includes educational content on optimizing data retrieval via indexing and transaction isolation levels.
Pigsty es una plataforma integral de orquestación de infraestructura de bases de datos diseñada para automatizar el ciclo de vida completo de clústeres de PostgreSQL de alta disponibilidad. Funciona como un framework de infraestructura como código que gestiona la coordinación de clústeres, el aprovisionamiento de nodos y el descubrimiento de servicios a través de playbooks idempotentes. Al integrar mecanismos de consenso distribuido, la plataforma garantiza la conmutación por error automatizada y la aplicación de estado consistente en diversos entornos, incluyendo infraestructura bare metal y virtualizada. La plataforma se distingue por un sólido conjunto de capacidades operativas que se extienden más allá de la gestión estándar de bases de datos. Cuenta con una tubería de observabilidad integrada que agrega métricas, registros y trazas en paneles centralizados para la monitorización del rendimiento en tiempo real y el análisis de diagnóstico. Además, proporciona un framework de migración que emula protocolos de cable propietarios y sintaxis SQL, permitiendo la integración de cargas de trabajo de bases de datos empresariales heredadas en entornos relacionales modernos. El sistema cubre una amplia superficie funcional, incluyendo gestión avanzada de almacenamiento con clonación de copia en escritura para un despliegue rápido, y orquestación de múltiples bases de datos que coordina motores relacionales con almacenamiento en caché y almacenamiento de objetos. También incorpora endurecimiento de seguridad, copia de seguridad y recuperación automatizadas, y enrutamiento de tráfico a través de proxies en capas para desacoplar las conexiones de los clientes de la topología del clúster subyacente. El proyecto se distribuye como un modelo de espejo de paquetes autónomo, lo que permite un despliegue y una gestión de dependencias consistentes en entornos seguros o aislados.
Tunes configuration parameters at the cluster, instance, or user level to optimize performance.
This project is a PostgreSQL Kubernetes operator and database orchestrator designed to automate the deployment, scaling, and lifecycle management of high-availability database clusters. It functions as a controller that uses declarative manifests to provision and synchronize the state of database instances within a cluster. The system manages high availability through streaming replication and ensures constant availability during maintenance via rolling updates. It also serves as a backup and recovery manager, handling point-in-time recovery, logical backups, and cluster cloning using cloud s
Offers database performance tuning via sidecar containers and storage volume resizing.
Pigsty is a full-stack orchestration suite for deploying, monitoring, and managing high-availability PostgreSQL clusters and their supporting infrastructure. It functions as a cluster management platform and high-availability suite that automates failover, manages virtual IPs, and ensures data consistency through distributed consensus. The project distinguishes itself by providing a comprehensive database infrastructure-as-code framework and a dedicated observability stack. It incorporates a backup and recovery manager supporting point-in-time recovery via S3-compatible object storage, alongs
Applies pre-defined tuning templates optimized for OLTP or OLAP workloads to maximize throughput.
This project is a comprehensive guide and collection of best practices for testing Node.js backend applications. It provides a curated set of patterns and reference examples for writing reliable unit, integration, and component tests. The project distinguishes itself through specific strategies for backend integration, including detailed methods for API contract testing against OpenAPI specifications and shared schemas. It offers specialized guidance on managing message queue testing, focusing on idempotency, resilience, and asynchronous event synchronization. The guide covers a broad range
Provides guidance on tuning database configuration flags to prioritize execution speed over durability during test runs.
This project is a collection of specialized toolsets for SQL Server, functioning as a diagnostic toolkit, performance monitor, and database administrator framework. It provides stored procedures and utilities designed to automate backup recovery, diagnose system health, and optimize database performance and indexing. The kit distinguishes itself through specialized capabilities for point-in-time restoration and the calculation of estimated data loss windows using backup history. It also includes an index optimizer that analyzes usage and size to provide prioritized recommendations for data re
Identifies resource-intensive queries and optimizes database indexes to improve system throughput.
pg_textsearch is a full-text search integration for PostgreSQL that provides large-scale text indexing and BM25 relevance ranking. It implements a scalable indexing architecture that uses a memtable system to spill data to disk segments, allowing for the processing of massive datasets. The project distinguishes itself through support for multilingual search via language-specific partial indexes and the ability to index complex expressions, such as JSONB fields or concatenated columns. It ensures high availability by utilizing PostgreSQL-native streaming replication and write-ahead logs to syn
Optimizes query speeds through segment consolidation, memory management, and skipping irrelevant data blocks.
SlateDB is a cloud-native key-value store and distributed database engine that utilizes a log-structured merge-tree architecture. It serves as a transactional storage layer designed to persist data directly to cloud object storage. The engine differentiates itself by optimizing read performance for remote storage through the use of bloom filters and multi-level block caching. It employs a single-writer multi-reader model and provides the ability to create zero-copy clones via copy-on-write checkpointing. The system supports atomic transactions, range queries, and snapshot-based concurrency c
Allows tuning of performance trade-offs between API request costs, durability latency, and cache utilization.