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NVIDIA/aistore

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1,880 星标·264 分支·Go·MIT·2 次浏览docs.nvidia.com/aistore↗

Aistore

AIStore: scalable storage for AI applications

Features

  • Data Storage Systems - Scales object storage for petascale deep learning.

Star 历史

nvidia/aistore 的 Star 历史图表nvidia/aistore 的 Star 历史图表

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常见问题解答

nvidia/aistore 是做什么的?

AIStore: scalable storage for AI applications

nvidia/aistore 的主要功能有哪些?

nvidia/aistore 的主要功能包括:Data Storage Systems。

nvidia/aistore 有哪些开源替代品?

nvidia/aistore 的开源替代品包括: blazegraph/database — This project is a high-performance semantic graph database engine designed for storing and querying massive RDF… apache/druid — Apache Druid is a real-time analytics database and distributed columnar time-series store designed for sub-second… apache/hudi — Apache Hudi is an open-source table format that brings ACID transactions, incremental processing, and multi-modal… apache/iceberg — Iceberg is an open table format and big data table manager designed for huge analytic datasets in cloud storage. It… apache/ignite — Ignite is a distributed in-memory data grid and compute platform. It functions as a distributed SQL database and… apache/arrow — Arrow is a cross-language development platform for in-memory data. It provides a standardized, language-independent…

Aistore 的开源替代方案

相似的开源项目,按与 Aistore 的功能重合度排序。
  • blazegraph/databaseblazegraph 的头像

    blazegraph/database

    985在 GitHub 上查看↗

    This project is a high-performance semantic graph database engine designed for storing and querying massive RDF datasets. It functions as a specialized platform for managing linked data and complex relationship models, utilizing standard semantic web protocols to integrate and analyze distributed information sources. The system distinguishes itself through its use of B-Tree indexing to enable rapid traversal of relationships within large-scale datasets and its support for the Triple Pattern Fragments protocol to facilitate scalable web-based access. It provides automated tools for transformin

    Javablazegraphgraph-databaserdf
    在 GitHub 上查看↗985
  • apache/druidapache 的头像

    apache/druid

    14,020在 GitHub 上查看↗

    Apache Druid is a real-time analytics database and distributed columnar time-series store designed for sub-second analytical queries. It functions as a data platform featuring a distributed SQL query engine and a real-time data ingestion system for moving historical and streaming data from external sources. The system is distinguished by its ability to provide low-latency analytics under high concurrency to power operational dashboards. It implements a Kerberos-secured environment for user authentication and employs a shared-nothing cluster architecture to enable horizontal scaling. The plat

    Javadruid
    在 GitHub 上查看↗14,020
  • apache/hudiapache 的头像

    apache/hudi

    6,097在 GitHub 上查看↗

    Apache Hudi is an open-source table format that brings ACID transactions, incremental processing, and multi-modal indexing to data lakes. It provides atomic commits with snapshot isolation, rollback, and optimistic concurrency control for reliable data lake operations, while supporting upserts, record-level updates, and deletions in large analytical datasets. The project distinguishes itself through a timeline-based architecture that coordinates all write operations, enabling features like time-travel querying, incremental change streaming, and multi-modal query views that include snapshot, i

    Javaapacheflinkapachehudiapachespark
    在 GitHub 上查看↗6,097
  • apache/arrowapache 的头像

    apache/arrow

    16,529在 GitHub 上查看↗

    Arrow is a cross-language development platform for in-memory data. It provides a standardized, language-independent columnar memory format designed to accelerate analytical operations and improve memory efficiency on modern computing hardware. By utilizing a schema-driven approach, the framework enables the efficient organization of both flat and nested data structures. The project functions as an analytical data processing engine that facilitates high-performance computation directly on memory-resident datasets. It distinguishes itself through a zero-copy architecture, which allows multiple

    C++arrowparquet
    在 GitHub 上查看↗16,529
查看 Aistore 的所有 25 个替代方案→