18 Repos
Techniques to maximize the volume of data updates per second using buffering and batching.
Distinct from Data Write Throughput Optimizers: Focuses on total write volume and throughput rather than just concurrency or specific buffering patterns.
Explore 18 awesome GitHub repositories matching data & databases · Write Throughput Optimizations. Refine with filters or upvote what's useful.
LevelDB is an embedded database library and persistent storage engine that provides a sorted key-value store. It uses a log-structured merge-tree architecture to map byte arrays to values, running directly within a process to provide storage without the need for a separate server process. The system is distinguished by its use of custom comparison functions to define key ordering, enabling efficient range scans and sequenced lookups. It ensures data reliability through atomic batch execution, consistent snapshot generation, and log-based recovery after failures. The engine covers broad capab
Uses atomic batches and asynchronous writes to handle large volumes of data updates efficiently.
MMKV is a high-performance, cross-platform key-value storage framework designed for mobile platforms and POSIX environments, including Android, iOS, macOS, and Windows. It provides a persistence layer that utilizes memory-mapped files and binary serialization to achieve low-latency data access. The project distinguishes itself through native support for multi-process synchronization, allowing concurrent read and write operations across different application processes. It also implements security via AES encryption for data at rest, featuring symmetric encryption and key rotation to protect st
Minimizes I/O operations by comparing new values against existing ones before committing writes to disk.
rqlite is a distributed relational database that replicates SQLite data across a cluster using the Raft consensus algorithm. It functions as a fault-tolerant storage system that provides high availability and a web API for executing SQL queries and managing relational data without requiring native database drivers. The system distinguishes itself by using an HTTP SQL interface to expose database operations and cluster management. It features a real-time change data capture stream that pushes database mutations to external HTTP endpoints via webhooks and supports the scaling of read throughput
Improves write performance using queued writes and maintains storage efficiency through automatic vacuuming.
FoundationDB is an ACID-compliant distributed transactional key-value store. It functions as a scalable database engine that ensures strict serializability and data consistency across a cluster of servers using a shared-nothing architecture. The system is distinguished by its multi-region replication capabilities, allowing data to be synchronized across different datacenters for high availability and disaster recovery. It utilizes optimistic concurrency control to manage distributed transactions and employs a majority-based coordination system to maintain cluster state. The platform provides
Allows choosing between a memory-optimized engine for small datasets or an SSD-optimized engine for larger ones.
Bolt is a single-file embedded key-value store for Go applications. It is an ACID transactional database that organizes data in B+trees on disk to provide efficient sorted key retrieval and range scans. The system uses a memory-mapped model to map the database file directly into the process address space for fast random-access reads. The project distinguishes itself through a multi-version concurrency control architecture that allows multiple simultaneous readers to access a consistent snapshot of data without blocking a writer. It employs a single-writer multi-reader locking model and uses a
Combines multiple write operations into single transactions to increase throughput and reduce disk commit overhead.
better-sqlite3 is a high-performance SQLite3 client for Node.js that executes queries synchronously, returning results directly without callbacks or promises. It compiles as a native addon using N-API, binding directly to the SQLite3 C library for immediate query execution and zero-copy result serialization into native JavaScript objects. The library is optimized for Write-Ahead Logging (WAL) mode, enabling faster concurrent reads and writes in web applications. It provides durability level tuning through the synchronous pragma, allowing adjustments between FULL, NORMAL, and OFF modes to bala
Improves read and write performance for concurrent database access by enabling Write-Ahead Logging.
Feast is an open-source feature store for machine learning that provides a central platform for defining, storing, and serving features across both training and inference workflows. It operates as a declarative system where feature definitions are written as code in Python files, synchronized to a central registry, and made available for low-latency online retrieval or point-in-time correct historical joins for training datasets. The project abstracts storage behind a pluggable architecture, allowing offline and online backends to be swapped without changing retrieval logic, and coordinates ma
Groups multiple insert queries into a single transaction to improve write throughput.
NLog is an open-source logging framework for .NET that functions as a structured logging library and log routing engine. It captures log events with named parameters as searchable data rather than plain text and directs these messages to various output destinations based on severity and source. The framework is designed as an extensible platform, supporting custom targets, layout renderers, and filters that can be loaded from external assemblies or defined in code. It features a dynamic configuration system that allows logging targets, rules, and layouts to be updated via XML or programmatic
Implements write throughput optimizations using buffering and batching to increase disk efficiency for log files.
Maddy is a modular mail server that assembles a complete email system by connecting small, single-purpose modules through a declarative configuration file. Rather than a monolithic stack, it lets operators compose message processing, storage, authentication, and security enforcement from interchangeable building blocks, with each module handling a specific function like receiving SMTP connections, verifying credentials, or applying policy checks. The server distinguishes itself through its flexible authentication and security architecture. It delegates user verification to external systems in
Configures SQLite WAL journal mode and autocheckpoint intervals to sustain high write throughput.
This is an open-source, crowd-sourced wiki textbook that teaches Linux system programming in C. It covers the core operating system concepts of process management through the fork-exec-wait model, dynamic memory allocation using implicit free list heap allocators, inode-based file systems, inter-process communication via pipes and shared memory, POSIX threads with synchronization primitives, signal-based asynchronous notification, virtual memory with page table translation, and runtime diagnostics using Valgrind and GDB. The textbook distinguishes itself by providing practical, implementation
Mentions splitting file content across disks for throughput as a conceptual topic.
Pebble is an embedded key-value storage engine written in Go, designed as a library that provides durable, write-optimized data persistence directly within applications. It organizes data using a log-structured merge-tree (LSM-tree) structure, where writes are first buffered in an in-memory skiplist memtable and persisted to a write-ahead log before being flushed to block-based SSTable files on disk. The engine supports atomic batch commits, configurable write synchronization, and automatic background compaction that merges and rewrites sorted runs to reclaim space and maintain read performanc
Designed for high write throughput using batched atomic commits and background compaction to reduce write amplification.
Raspotify ist ein Headless-Audio-Streamer für Linux-Geräte, der als Spotify-Connect-Client fungiert. Er arbeitet als Hintergrund-System-Daemon und ermöglicht es Hardware, als drahtloser Audioempfänger zu fungieren, der über die offizielle Spotify-Anwendung steuerbar ist. Der Dienst ist für Einplatinencomputer konzipiert und beinhaltet eine Minimierung von Festplattenschreibvorgängen, um den Verschleiß von SD-Karten zu reduzieren. Dies wird erreicht, indem Audio-Track-Buffer auf ein In-Memory-Dateisystem umgeleitet werden. Das Projekt enthält Funktionen zur Konfiguration der Audioqualität, einschließlich Anpassungen von Bitrate und Samplerate. Es verwaltet zudem die Authentifizierung durch lokales Token-Caching, um persistente Verbindungen ohne wiederholte Login-Vorgänge aufrechtzuerhalten.
Reduces physical disk writes by buffering track downloads in system memory rather than on the SD card.
OpenTSDB ist eine verteilte Zeitreihendatenbank und Metrics-Engine, die für die Speicherung und Verwaltung massiver Mengen hochkardinaler Systemmetriken entwickelt wurde. Es fungiert als Datenspeicher und Analyseplattform, die groß angelegte Metrik-Ingestion und Infrastruktur-Performance-Monitoring über einen verteilten Cluster hinweg ermöglicht. Das System zeichnet sich durch eine verteilte Speicherabstraktion aus, die mehrere Backends wie HBase, Cassandra und Google Bigtable unterstützt. Es nutzt einen hierarchischen Metrikbaum zur Organisation von Zeitreihen und verwendet numerische Identifikator-Indizierung, um den Speicherbedarf zu reduzieren und Suchvorgänge für getaggte Metriken zu beschleunigen. Das Projekt deckt breite Funktionsbereiche ab, einschließlich Zeitreihendatenanalyse mit verteilten Perzentilberechnungen und Downsampling sowie umfassendem Metadatenmanagement. Es bietet API-Integration für Datenaufnahme und -abfrage, Off-Heap-Caching zur Performance-Optimierung sowie Tools für die Datenintegritätsprüfung und Anomalieanalyse. Das System wird über eine Kommandozeilenschnittstelle für die Datenbankadministration und die Synchronisation des Metrikbaums verwaltet.
Arranges data based on timestamps to reduce disk reads and minimize background merge overhead.
ipscan is a cross-platform network auditor and Java-based network scanner used for discovering networked devices and exporting scan results. It functions as an IP address range scanner and a TCP/UDP port scanner to identify active hosts and open services on a network. The application features a plugin-based fetcher architecture that allows the integration of custom data collection fetchers to retrieve specific hardware or software information from discovered hosts. Its broader capabilities include local network discovery, network port auditing, and the creation of network asset inventories.
Implements disk-buffered writing to export large scan datasets without causing memory overflow.
Dieses Projekt ist ein umfassendes MySQL-Datenbank-Tutorial und eine instruktive Ressource, die für Anfänger konzipiert ist. Es dient als technisches Handbuch und Lernleitfaden, der Installation, Konfiguration und Betrieb eines relationalen Datenbankmanagementsystems abdeckt. Die Materialien bieten einen strukturierten Ansatz für die Grundlagen relationaler Datenbanken, einschließlich Schema-Design, Tabellenerstellung und der Ausführung von SQL-Queries. Es enthält spezifische Anleitungen zur Datenbankadministration, wie das Verwalten von Benutzerzugriffen, das Konfigurieren von Storage-Engines und die Handhabung der Server-Installation über verschiedene Betriebssysteme hinweg. Die Ressource deckt ein breites Spektrum an Funktionen ab, einschließlich Datenmanipulation für temporale Daten und Unicode-Zeichen, Client-Server-Konnektivität und Datenbank-Lifecycle-Management. Sie bietet zudem diagnostische Informationen für die System-Fehlersuche, um Installationskonflikte und Startfehler zu beheben. Der Inhalt wird als Sammlung Markdown-basierter Dokumentation bereitgestellt, die schrittweise prozedurale Anleitungen und beispielgesteuerte Query-Demonstrationen enthält.
Explains how to optimize data storage on disk by selecting and configuring appropriate MySQL storage engines.
This repository is a collection of technical knowledge and solutions focused on mobile application development, particularly for Android and iOS platforms. It covers a wide range of practical engineering challenges, including hotfix and patching techniques, database management and repair, network communication, logging, and video processing. The content is presented as shared knowledge, documenting real-world problems and their implementations. The project provides detailed guidance on applying hotfixes to running Android applications through multiple methods, such as class replacement, full
Details techniques for optimizing SQLite database performance on iOS platforms.
Toshi is a full-text search engine and library implemented in Rust, designed to manage and query large-scale structured datasets. It functions as a distributed search platform that enables high-speed information retrieval across massive collections of data. The system distinguishes itself through an architecture built for high-throughput ingestion and parallel query execution. It utilizes an actor-model concurrency framework to coordinate worker processes and employs distributed sharding to partition index segments across multiple nodes. To maintain performance and data integrity, the engine
Allows tuning of memory allocation, thread counts, and buffers to maximize the efficiency of document ingestion.
XlsxWriter is a library for generating spreadsheets in the XLSX format, functioning as an Excel workbook writer and file generator. It provides the capability to write data, apply cell formatting, and build complex layouts across multiple worksheets. The project distinguishes itself with a memory-optimized writing mode that flushes large datasets to disk row-by-row, enabling the creation of files exceeding 4 GB while minimizing RAM consumption. It also includes a specialized mechanism for embedding binary project files and digital signatures to enable VBA macros and signed scripts within work
Uses a specialized processing mode to lower memory consumption when generating spreadsheets with massive datasets.