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5 Repos

Awesome GitHub RepositoriesStorage Lifecycle Management

Automated policies for managing data placement and migration across storage tiers.

Distinguishing note: Focuses on automated tiering based on access frequency.

Explore 5 awesome GitHub repositories matching data & databases · Storage Lifecycle Management. Refine with filters or upvote what's useful.

Awesome Storage Lifecycle Management GitHub Repositories

Finde die besten Repos mit KI.Wir suchen mit KI nach den am besten passenden Repositories.
  • seaweedfs/seaweedfsAvatar von seaweedfs

    seaweedfs/seaweedfs

    32,937Auf GitHub ansehen↗

    SeaweedFS is a distributed object store and high-performance file system designed to manage massive volumes of unstructured data. It utilizes a decoupled architecture that separates metadata management from raw data storage, allowing for independent scalability and the efficient handling of billions of files. By providing a POSIX-compliant interface, it enables applications to interact with a unified namespace while maintaining the performance characteristics of a distributed object store. The system distinguishes itself through a multi-region data fabric that supports active-active replicati

    Moves data between different storage media types based on access frequency to optimize cost and performance.

    Goblob-storagecloud-drivedistributed-file-system
    Auf GitHub ansehen↗32,937
  • apify/crawleeAvatar von apify

    apify/crawlee

    24,002Auf GitHub ansehen↗

    Crawlee is a web scraping framework designed for building scalable, reliable, and distributed data extraction pipelines. It provides a unified interface for managing headless browser automation and lightweight HTTP requests, allowing developers to handle complex web navigation, dynamic content rendering, and large-scale data collection within a single, modular architecture. The project distinguishes itself through its resource-aware concurrency controller, which dynamically scales task execution based on real-time CPU and memory usage to prevent host machine exhaustion. It also features a rob

    Provides lifecycle management for data stores to maintain clean persistence for crawler runs.

    TypeScriptapifyautomationcrawler
    Auf GitHub ansehen↗24,002
  • stas00/ml-engineeringAvatar von stas00

    stas00/ml-engineering

    18,124Auf GitHub ansehen↗

    This project is a comprehensive engineering framework and technical reference for managing, scaling, and optimizing distributed machine learning infrastructure. It provides a suite of methodologies and diagnostic tools designed to support large-scale model training and inference on high-performance computing clusters. The project distinguishes itself through a specialized diagnostic toolkit and infrastructure optimization suite that addresses the complexities of multi-node environments. It enables precise control over cluster resources, including hardware maintenance, network topology configu

    Configures tiered storage solutions for hot, warm, and cold data to optimize costs and ensure availability during cluster migrations.

    Pythonaidebugginggpus
    Auf GitHub ansehen↗18,124
  • apache/pinotAvatar von apache

    apache/pinot

    6,098Auf GitHub ansehen↗

    Pinot is a distributed, columnar analytical database designed for high-concurrency, low-latency query processing. It functions as a real-time OLAP datastore, enabling interactive, user-facing analytics by ingesting and querying massive datasets from both streaming and batch sources. The system architecture relies on a centralized controller for cluster coordination and a distributed segment-based storage model to ensure horizontal scalability. The platform distinguishes itself through a hybrid ingestion pipeline that unifies real-time event streams and historical batch data into a single quer

    Deletes specific or expired query result sets to free up storage and maintain system performance.

    Java
    Auf GitHub ansehen↗6,098
  • ravendb/ravendbAvatar von ravendb

    ravendb/ravendb

    3,961Auf GitHub ansehen↗

    RavenDB is a multi-model NoSQL document database designed for high-performance, ACID-compliant data storage. It persists structured information as schema-flexible JSON documents and utilizes a unit-of-work session pattern to track entity changes and batch modifications into atomic transactions. The platform is built on a distributed architecture that supports horizontal scaling through sharding and ensures high availability via multi-node, master-to-master cluster replication. The database distinguishes itself through a self-optimizing query engine that automatically creates and maintains ind

    Automates the archival, expiration, and versioning of data to ensure compliance and storage efficiency.

    C#csharpdatabasedocument-database
    Auf GitHub ansehen↗3,961
  1. Home
  2. Data & Databases
  3. Storage Lifecycle Management

Unter-Tags erkunden

  • Cluster Scaling & RecoveryManagement of the physical and logical size of storage clusters and their recovery from failure. **Distinct from Storage Lifecycle Management:** Focuses on cluster-level lifecycle (creation, resizing, recovery) rather than automated data tiering policies.
  • Query Result Lifecycle ManagersAutomated deletion of expired query result sets to maintain system performance. **Distinct from Storage Lifecycle Management:** Distinct from Storage Lifecycle Management: focuses on query result set expiration rather than data tiering.