# Installer vineyard avec Homebrew Consultez les chemins d'installation, exécutables, métadonnées et notes de sécurité de vineyard pour les workflows d'agents IA. ## installation ```sh sudo av install brew:vineyard ``` Commandes d'installation supplémentaires: ### macOS - Homebrew (100%): ```sh brew install vineyard ``` Preuve: local Homebrew formula metadata ## Faits du paquet - **Clé du paquet:** brew:vineyard - **Gestionnaire de paquets:** Homebrew - **Version:** 0.24.4 - **Résumé source:** In-memory immutable data manager. (Project under CNCF) - **Page d'accueil:** - **Dépôt:** - **Dernière mise à jour:** 2026-07-14T20:07:13+09:00 - **Généré:** 2026-08-03T19:37:03+00:00 ## exécutables - vineyard-graph-loader (alias) - vineyardd (alias) ## Comportement d'installation - Bouteille: non disponible ## Version et fraîcheur - page générée: 2026-08-03 - version du gestionnaire: 0.24.4 ## Historique du projet et usages Vineyard, also styled v6d, is an in-memory immutable data manager for sharing distributed data between analytics systems without copying it through files or serialization layers. Its own documentation frames it as infrastructure for graph analytics, numerical computing, and machine-learning workflows where intermediate data must move between engines such as GraphScope, Mars, PyTorch, Spark, Hive, Airflow, Flyte, Kubeflow Pipelines, and Kubernetes-native jobs. ### Historique du projet The public GitHub repository was created in October 2020, and the project entered the Cloud Native Computing Foundation sandbox on April 28, 2021. CNCF annual reviews describe the original maintainer base as Alibaba-led, with early focus on high-level distributed objects such as tensors, tables, graphs, and streams, plus polyglot SDKs for C++, Python, and Java. By the 2023 CNCF review, Vineyard had expanded its language and workflow surface to include Python, Go, Rust, Java, Kubernetes integration, workflow-engine integrations, and an academic paper, 'Vineyard: Optimizing Data Sharing in Data-Intensive Analytics,' published at SIGMOD 2023. The project presented itself as a cloud-native object store for complex AI and analytics pipelines where intermediate data exchange is a bottleneck. ### Historique d'adoption CNCF review documents report early adoption and evaluation in GraphScope, Mars-related workflows, the ESRF BLISS environment, and PingAn research platforms. The 2023 review says PingAn Tech had moved Vineyard into production for dataset sharing and management, while StartDT/Qidianyun was evaluating it for Python-centric data processing pipelines. The same CNCF reviews show community growth from the sandbox entry period into 2023, including a reported move from roughly 26 to 40 contributors and from 600-plus to about 750 GitHub stars between the 2022 and 2023 annual reviews. Those figures are self-reported by the project in CNCF governance material rather than independent market-share data. ### Modes d'utilisation In practice, Vineyard is used as a shared-memory/object-store layer between steps in a data workflow. A producer writes distributed dataframes, tensors, graphs, streams, or other registered object types into Vineyard; consumers in other systems retrieve those objects by id and operate on them without the usual copy-heavy detour through external storage. Its package-nerd niche is cloud-native data plumbing: the command-line and daemon pieces matter less as user-facing utilities than as the runtime substrate behind Python APIs, Kubernetes operators, scheduler plugins, workflow integrations, and data-system connectors. ### Chronologie - 2020-10: The v6d-io/v6d repository was created on GitHub. - 2021-04-28: Vineyard was accepted as a CNCF sandbox project. - 2022: CNCF annual review described adoption in GraphScope, Mars-related workflows, ESRF BLISS testing, and PingAn testing. - 2023-06: The Vineyard SIGMOD paper was published with DOI 10.1145/3589780. - 2023: CNCF annual review described PingAn production use, StartDT evaluation, and expanded workflow/Kubernetes integrations. ### Related projects - Vineyard is closely related to GraphScope, Mars, PyData-style dataframe/tensor workflows, Kubernetes, Kubeflow Pipelines, Airflow, Flyte, Spark, Hive, and the CNCF data/batch ecosystem. ### Sources - - - - - ## Notes de sécurité narrow executable package without higher-risk signals. - **Risque Geiger:** vert / faible - narrow executable package without higher-risk signals ## Combined YAML source View the package source record on GitHub. [combined/vineyard.yml](https://github.com/mxcl/pkgdb/blob/main/combined/vineyard.yml) ## Sources - pkg.so package database - Geiger risk classifier - curated package history - pkgdb category and tag curation - cross-ecosystem install command graph