8 dépôts
Storage engines that organize data into immutable, compressed chunks for efficient access.
Distinguishing note: Focuses on the storage format and structure rather than the query engine.
Explore 8 awesome GitHub repositories matching data & databases · Log-Structured Storage. Refine with filters or upvote what's useful.
InfluxDB is a specialized time series database platform engineered for the high-speed ingestion, compression, and retrieval of timestamped data at scale. It functions as a distributed metrics platform, providing the infrastructure necessary to organize and analyze massive volumes of time-stamped information to identify trends, patterns, and anomalies within complex data streams. The platform distinguishes itself through a functional dataflow engine that utilizes a specialized programming language for complex analytical transformations and automated tasks. This architecture is supported by a p
Organizes incoming data into sorted immutable files to optimize write throughput and range-based queries.
Loki is a horizontally scalable, highly available log aggregation engine designed to store and query massive volumes of unstructured log data. It functions as a distributed observability platform that correlates logs, metrics, and traces to provide comprehensive visibility into the health and performance of complex infrastructure. The system distinguishes itself through a distributed query execution model that processes large datasets in parallel across cluster nodes. It utilizes label-based stream indexing and a distributed index to map log data to specific chunks, enabling rapid retrieval w
Compresses and stores data in immutable chunks within object storage.
TDengine is a distributed time-series database designed for the high-speed ingestion, compression, and retrieval of timestamped metrics and sensor data. It functions as a SQL-compatible analytics engine, allowing users to perform complex operations on massive volumes of time-ordered information using standard relational syntax. The platform is built to serve as a backend foundation for industrial IoT environments, managing real-time data streams and device metadata through a cluster-based architecture. The system distinguishes itself through a distributed sharding architecture that uses consi
Appends incoming data to memory-resident buffers and sequential log files to minimize disk seek latency during writes.
This project serves as a comprehensive technical reference for the architecture and design of data-intensive applications. It provides a structured analysis of the fundamental principles required to build reliable, scalable, and maintainable software systems, covering the core trade-offs inherent in modern data infrastructure. The repository explores the mechanics of distributed data management, including strategies for replication, partitioning, and achieving consensus across multiple nodes. It details the design of storage engines, indexing techniques, and transaction management models, whi
Organizes data into immutable, compressed chunks for efficient access in storage engines.
Neon is a serverless PostgreSQL database platform designed with a decoupled storage and compute architecture. It functions as a multi-tenant system that isolates data and compute resources for independent users on shared cloud infrastructure, utilizing a specialized PostgreSQL storage engine. The platform features a database branching system that allows for the creation of isolated, instant copies of a database for testing and development. It further distinguishes itself with an HTTP-based SQL gateway, enabling the execution of queries via HTTP requests and JSON responses without the need for
Utilizes a log-structured storage engine to persist write-ahead logs to remote object storage.
This project is a curated directory of software, frameworks, and educational resources designed for building, scaling, and maintaining distributed data processing and storage architectures. It serves as a comprehensive index for the distributed computing ecosystem, helping users identify the appropriate tools for managing large-scale information systems. The repository functions as a central hub for data engineering, offering categorized access to technologies that support batch and stream processing, machine learning, and interactive querying. By organizing these resources, it assists in the
Uses append-only file structures to optimize write throughput and retrieval in distributed storage systems.
This project is a curated collection of academic papers, books, and technical resources designed for studying the architecture and implementation of database management systems. It serves as a comprehensive educational guide for engineers and researchers looking to understand the fundamental principles behind modern data storage and retrieval. The repository distinguishes itself by providing structured learning paths across critical database domains, including the design of persistent storage engines, the mechanics of query optimization, and the complexities of distributed transaction managem
Provides documentation on log-structured storage engines that use sequential appends to optimize write performance and recovery.
Fluvio est une plateforme de streaming d'événements distribuée et un moteur de streaming cloud-native conçu pour collecter, persister et répliquer des flux de données en temps réel à travers un cluster distribué. Il fonctionne comme un pipeline de données temps réel pour construire des workflows avec état qui ingèrent, enrichissent et exportent des données entre des sources et des destinations externes. La plateforme se distingue par son utilisation de WebAssembly pour exécuter des modules compilés pour des transformations et filtrages de données en ligne. Cela permet l'exécution d'une logique métier personnalisée pour remodeler l'information en mouvement sans nécessiter de redémarrage du cluster. Le système couvre un large éventail de capacités, incluant l'ingestion de données basée sur des connecteurs depuis des protocoles externes, un stockage immuable structuré en logs avec E/S zéro-copie, et une mise à l'échelle horizontale du cluster. Il prend en charge la création de pipelines complexes pilotés par les événements qui utilisent le traitement avec état, les agrégations par fenêtrage et la distribution de données basée sur les partitions. Le moteur peut être déployé comme un binaire léger sur diverses architectures système, y compris des appareils IoT ARM64 pour le traitement de données en périphérie (edge).
Uses a log-structured storage engine to save immutable, append-only message segments for high-performance writes.