29 repositorios
Scalable architectures that aggregate multiple independent nodes into a single unified storage system.
Explore 29 awesome GitHub repositories matching software engineering & architecture · Distributed Storage Clusters. Refine with filters or upvote what's useful.
This project is a comprehensive Java backend engineering guide and technical reference focused on high-concurrency design, distributed systems, and microservices architecture. It provides detailed strategies for decomposing monolithic applications, managing service discovery, and implementing the architectural patterns required for scalable backend environments. The repository distinguishes itself through an extensive collection of big data algorithmic references and database scaling strategies. It covers memory-efficient techniques for analyzing massive datasets, such as Top-K element extrac
The system distributes data across multiple nodes using a built-in cluster mode without relying on client-side sharding.
MinIO is a software-defined, cloud-native object storage server designed to manage large volumes of unstructured data. It functions as a distributed storage cluster that aggregates multiple independent nodes into a unified, scalable pool, providing a high-performance infrastructure compatible with standard cloud storage protocols and application programming interfaces. The system utilizes a shared-nothing architecture that eliminates central metadata servers, relying instead on a decentralized hash table to map objects across the cluster. Data availability and resilience are maintained throug
Aggregates multiple independent nodes into a single, unified, and resilient storage system.
Rustfs is a distributed object storage system designed for high availability and horizontal scalability. It functions as a cluster-based platform that manages data across multiple nodes, providing a self-hosted infrastructure for large-scale storage requirements. The system is built to be container-native, utilizing an operator to automate deployment and management within orchestrated environments. It provides compatibility with standard object storage protocols, allowing existing applications and tools to interact with the storage layer through a translation interface. To ensure long-term re
Functions as a distributed storage system that scales horizontally across nodes for high availability and fault tolerance.
This project is a human resources management system built using Spring Boot and Vue. It serves as a platform for managing employee records, professional titles, and organizational hierarchies. The system features a role-based access control framework that maps users to specific roles and resources to secure API endpoints and user interface elements. It includes a real-time communication hub utilizing WebSockets for internal corporate chat and system notifications, as well as a dedicated manager for defining and modifying nested organizational department structures. Additional capabilities co
Integrates with distributed file systems to store and manage corporate documents across multiple storage servers.
NATS Server is a high-performance, lightweight messaging system designed for cloud-native applications, edge computing, and distributed microservices. It functions as a distributed publish-subscribe broker that routes messages using hierarchical, dot-separated subject strings, enabling decoupled communication between services without requiring centralized broker lookups. The system supports core messaging patterns including asynchronous publish-subscribe, request-reply, and load-balanced queue processing. The platform distinguishes itself through a decentralized architecture that eliminates t
Connects multiple server instances into a unified network to share message traffic and provide horizontal scalability across different nodes.
This project is a containerized orchestration layer for the Elastic Stack, providing a pre-configured set of Docker Compose files to deploy Elasticsearch, Logstash, and Kibana as a unified data analysis stack. It functions as a centralized log management system for ingesting, indexing, and searching log data using a cluster of interconnected services. The deployment pattern includes an Elasticsearch cluster manager that enables scaling data nodes through replica scaling and internal discovery. It provides a web-based administration interface for monitoring cluster health and status. The syst
Aggregates multiple nodes into a unified storage system to increase capacity and availability.
BigData-Notes is a big data learning resource and data engineering knowledge base. It provides a collection of guides, technical references, and documentation focused on the installation and configuration of distributed data processing technologies. The project covers a learning path for distributed systems, including the setup of large-scale data storage and computing clusters. It specifically addresses both batch and stream processing workflows and the implementation of data APIs for interacting with distributed messaging and storage systems. The materials are organized using markdown-base
Provides technical references and setup instructions for managing large-scale distributed storage clusters.
TiKV is a distributed transactional key-value store designed for horizontal scalability and high availability. It functions as a storage engine that maintains massive datasets across a cluster of physical nodes, ensuring that information remains accessible and consistent even when individual hardware components fail. The system utilizes a consensus-based replication model to synchronize data across nodes, ensuring that all replicas agree on the order of operations. It manages data distribution through a sharding mechanism that partitions large datasets into smaller groups, each governed by in
Maintains massive datasets across a cluster of nodes to provide scalable and low-latency storage for large-scale deployments.
VictoriaMetrics is a high-performance, scalable time series database and observability platform designed for long-term storage and analysis of metric, log, and trace data. It functions as a unified backend for monitoring ecosystems, offering full compatibility with industry-standard protocols and query languages. The system is built to handle massive data volumes through a distributed architecture that supports horizontal scaling and efficient data lifecycle management. The platform distinguishes itself through a storage engine that utilizes consistent hashing for data sharding and log-struct
Installs multi-component cluster architectures to manage and scale large volumes of time series data.
Ceph is a unified, software-defined storage platform designed to provide object, block, and file storage services from a single distributed cluster. By decoupling data management from physical hardware, it enables elastic scaling across commodity hardware, allowing organizations to build large-scale storage infrastructure without reliance on proprietary vendor equipment. The system distinguishes itself through a shared-nothing, distributed architecture that utilizes deterministic hashing for data placement. This approach eliminates centralized metadata bottlenecks, allowing the cluster to sca
Aggregates multiple independent nodes into a single unified storage system for enterprise-scale data management.
Hadoop is a big data infrastructure suite and distributed data processing framework designed to store and process massive datasets across clusters of computers. It consists of a distributed storage system for managing large files across multiple nodes and a parallel computing engine for processing data across a distributed cluster. The framework implements a distributed file system to ensure fault tolerance and high throughput, paired with a programming model that processes large datasets in parallel. It manages the underlying hardware and software environment required for distributed big dat
Implements a scalable distributed file system that manages large files across multiple nodes for fault tolerance.
phpredis is a C-based native extension that bridges PHP applications with Redis servers for high-performance data storage and retrieval. It serves as an interface for manipulating strings, hashes, lists, sets, and sorted sets while providing a direct path for executing Redis commands and server-side scripts. The extension provides comprehensive support for distributed environments and high availability. It interfaces with Redis Cluster to distribute data across multiple nodes using hash slots and manages Redis Sentinel for service discovery and automatic failover. It also enables shared state
Provides native support for Redis Clusters, distributing data and requests across multiple nodes.
3FS is a distributed file system and RDMA storage cluster designed for high-performance AI training and inference workloads. It functions as a strongly consistent storage layer that utilizes a disaggregated architecture to pool SSDs and memory resources across multiple nodes. The system provides specialized storage implementations including an AI training checkpoint store for parallel state preservation and a distributed key-value cache store for decoder layer vectors to optimize inference processing. It ensures data integrity through chain replication and apportioned query distribution. The
Implements a disaggregated distributed storage cluster using RDMA and SSDs to provide high-throughput data transfers for AI workloads.
FastDFS is a distributed file system and object store designed as a high-capacity file server. It functions as a cluster storage manager that saves, syncs, and accesses large volumes of unstructured data across a network of distributed servers. The system uses unique identifiers for file retrieval and indexing instead of traditional hierarchical naming to avoid metadata bottlenecks. It manages file attributes through key-value metadata mapping and employs a distributed replication model to ensure high availability and data redundancy across storage groups. The project provides capabilities f
Functions as a high-performance distributed file system for saving, syncing, and accessing files across a cluster of servers.
dockerlabs is a collection of educational labs and technical tutorials designed to teach the fundamentals of containerization and microservice architecture. It provides instructional material and hands-on exercises covering image optimization, security training, infrastructure setup, and cluster orchestration. The project features specific courses and guides focused on reducing image size through multi-stage builds, securing workloads via vulnerability scanning and encrypted networks, and deploying multi-node clusters with high availability using Swarm orchestration. The materials cover a br
Instructs on configuring volumes and drivers to ensure data persistence across multi-node cluster environments.
Hazelcast is a distributed data platform that combines an in-memory data grid with a stream processing engine to support real-time analytics and event-driven applications. It functions as a partitioned, distributed key-value store that replicates data across cluster nodes to provide low-latency access and high availability. The platform also serves as a distributed SQL query engine, allowing users to execute standard SQL statements against both in-memory datasets and external data sources. What distinguishes Hazelcast is its use of a distributed consensus subsystem to maintain strongly consis
Provides automated recovery mechanisms to merge partitioned cluster segments and restore a unified system state.
Pachyderm is a containerized, versioned, and lineage-tracked data pipeline platform that runs natively on Kubernetes. It combines a distributed file system backend with immutable data versioning, so every commit to a data repository creates an auditable snapshot, and every pipeline step executes as an isolated container. The platform is defined by a data-centric pipeline model where pipelines are specified by their input and output data repositories rather than explicit task sequences, and provenance is recorded as a directed acyclic graph of commits linking output data to its input sources an
Data is stored and versioned on a distributed file system (PFS), providing scalable, fault-tolerant storage for large datasets.
PikiwiDB es una base de datos NoSQL distribuida y almacén de clave-valor basado en disco que sirve como servidor de protocolo compatible con Redis. Está diseñado para manejar datasets más grandes que la memoria disponible del sistema utilizando un motor de persistencia que almacena el dataset completo en disco. El sistema emplea un modelo de almacenamiento por niveles, almacenando en caché los datos calientes accedidos frecuentemente en memoria mientras mantiene el volumen principal en disco. Asegura una alta disponibilidad a través de una arquitectura de almacén de datos replicado, utilizando logs binarios asíncronos para sincronizar datos entre nodos primarios y secundarios. El proyecto soporta el escalado de bases de datos distribuidas mediante sharding de datos basado en clusters y organiza los datos en grupos para expandir la capa de almacenamiento. Sus capacidades operativas incluyen monitoreo del rendimiento del sistema para rastrear la utilización de recursos y soporte para despliegue contenedorizado.
Organizes data into groups using a distributed storage cluster architecture to elastically scale the storage layer.
JanusGraph is a distributed, elastically scalable graph database designed to store and query highly connected data across a cluster of machines. It supports the property graph data model with ACID consistency and integrates multi-model search capabilities including geo, numeric range, and full-text queries. The database also includes a Graph OLAP engine for running batch analytics and global graph computations on large datasets using the Hadoop framework. The project distinguishes itself through a masterless cluster architecture that eliminates single points of failure, allowing every node to
Distributes vertices and edges across multiple machines so the graph grows with the cluster size.
LXD is a unified platform for managing both system containers and virtual machines through a single REST API and command-line interface. It provides a programmatic HTTP interface for controlling the full lifecycle of instances, enabling automation and integration with external tools. The system runs unprivileged containers with per-instance UID/GID mappings, seccomp filters, and AppArmor profiles for kernel-level isolation, while supporting multiple storage backends including directory, Btrfs, LVM, ZFS, Ceph, LINSTOR, and TrueNAS through a unified driver interface. The platform distinguishes
Shares remote block devices across cluster members using distributed LVM locking.