7 Repos
Utilities and methodologies for measuring and comparing database execution speeds and resource utilization.
Distinct from Database Performance Utilities: Distinct from Database Performance Utilities: focuses on the act of measuring and quantifying performance rather than the tools used to optimize it.
Explore 7 awesome GitHub repositories matching data & databases · Performance Benchmarking. Refine with filters or upvote what's useful.
This is a reference implementation library providing a collection of code samples, Transact-SQL scripts, and schemas for SQL Server, Azure SQL, and Azure Synapse. It focuses on providing standardized implementation patterns and reference code for building relational databases and cloud data warehouses. The library distinguishes itself by offering specialized guides and examples for deploying database instances within containerized environments and Azure cloud services. It includes specific reference databases and language extensions for integrating machine learning services and advanced analy
Implements performance testing to measure memory and disk retrieval speeds for optimizing data processing.
TechEmpower FrameworkBenchmarks is an open-source project that provides a standardized, reproducible suite for measuring and comparing the performance of web frameworks across many languages. At its core, it defines a set of common server-side tasks—such as JSON serialization, database queries, and server-side template rendering—and executes them uniformly against hundreds of framework implementations to produce comparable throughput and latency metrics. The project is built around a multi-language benchmark harness that automates the full test lifecycle, from dependency installation and serve
Tests measuring database read, write, and query performance across multiple database backends.
This project is a suite of analytical tools for quantifying web performance, specifically designed for benchmarking the rendering speed and memory usage of various JavaScript frameworks. It provides a standardized set of DOM manipulation tests and a comparison tool that uses weighted geometric means to measure efficiency across different web implementations. The benchmark harness distinguishes itself by providing deep analysis of DOM reconciliation strategies, comparing the performance and correctness of keyed versus non-keyed rendering. It also includes a memory profiler for tracking allocat
Provides a reporting system that compares the speed and scalability of different web framework implementations.
This project is a web framework performance benchmark suite and automated benchmarking orchestrator. It serves as a multi-language performance analysis tool designed to measure execution speed, throughput, and latency across various HTTP libraries and programming ecosystems. The system functions as an HTTP framework comparison tool that evaluates relative efficiency using consistent hardware and request patterns. It automates the build, deployment, and execution cycles necessary to collect stable performance data and compute metrics such as error rates and latency percentiles. The suite eval
Provides standardized benchmarks to compare the speed and scalability of different web frameworks.
sysbench is a database and system benchmark tool used to measure the throughput and latency of database systems and hardware components. It functions as a multi-threaded workload generator and hardware performance profiler designed to determine how systems perform under heavy load. The project serves as a scriptable benchmark engine, allowing for the definition of custom performance scenarios through scripts. It simulates real-world traffic patterns by generating random data based on mathematical probability distributions, such as Zipfian, Gaussian, or Pareto. Capabilities cover database per
Measures throughput and latency by running synthetic workloads and transactions against database systems to test speed and scalability.
Dieses Projekt bietet einen Header-only C++-Wrapper für die Node-API und dient als Framework für den Aufbau leistungsstarker nativer Addons für Node.js. Es fungiert als Brücke zwischen C++ und JavaScript und bietet eine objektorientierte Schnittstelle, die die Erstellung kompilierter Erweiterungen vereinfacht und gleichzeitig die Komplexität der Sprachgrenze verwaltet. Die Bibliothek zeichnet sich durch die Bereitstellung typsicherer Abstraktionen für Data-Marshalling und Speicherverwaltung aus, wodurch sichergestellt wird, dass native und Skript-seitige Objekte korrekt verfolgt und freigegeben werden. Sie enthält Mechanismen zur Koordination asynchroner Aufgaben zwischen Hintergrund-Threads und dem Haupt-Event-Loop, um Datenkorruption zu verhindern und gleichzeitig intensive Berechnungen auszulagern. Darüber hinaus ordnet sie native Ausnahmen (Exceptions) Standard-Skript-Fehlertypen zu, was eine konsistente Diagnoseberichterstattung und Fehlerbehandlung sicherstellt. Über ihre Kern-Brückenfunktionen hinaus unterstützt das Projekt den gesamten Lebenszyklus der nativen Entwicklung, einschließlich der Bereitstellung von C++-Klassen und -Methoden für die JavaScript-Laufzeit. Es bietet Tools zur Verwaltung von Umgebungs-Lebenszyklen, zur Automatisierung von Code-Migrationen und zur Durchführung von Leistungsbenchmarks, um das Verhalten nativer Komponenten zu bewerten.
Provides utilities for measuring and comparing the performance of native code components.
Realm Kotlin is a local, object-oriented NoSQL database engine designed for Kotlin Multiplatform applications. It enables developers to persist structured application data directly as objects, eliminating the need for traditional relational table structures while ensuring information remains accessible during offline periods. The library distinguishes itself through a compiler-plugin-based architecture that maps standard language classes to database models at compile time. It utilizes zero-copy memory mapping and a lazy-loading query engine to manage data efficiently, while a shared C++ core
Includes integrated microbenchmarking tools for mobile devices to track execution speed and identify performance bottlenecks.