{"categories":[{"label":"Libraries","url":"https://skillfed.io/packages/category/software-development-libraries/9"},{"label":"Distributed Computing","url":"https://skillfed.io/packages/category/system-distributed-computing/3"}],"enrichment":{"capability":"Vineyard is an in-memory immutable data manager that enables zero-copy sharing of distributed data across big data systems like graph analytics, numerical computing, and machine learning frameworks.","skillfed_tags":["distributed-data","zero-copy-sharing","big-data-pipeline"],"use_cases":["Preprocessing large datasets and training models without intermediate file I/O.","Sharing distributed graphs and tensors across graph analytics engines.","Building data pipelines where multiple frameworks need to exchange immutable data structures with minimal overhead.","Reducing memory-copy and I/O costs in multi-stage big data workflows on distributed clusters.","Integrating numerical computing with machine learning frameworks in a single logical pipeline."],"what_it_does":"Vineyard is an in-memory immutable data manager designed to solve the data-sharing bottleneck in distributed big data pipelines. It provides zero-copy sharing of complex data structures (dataframes, tensors, graphs) across different systems via shared memory, eliminating serialization, deserialization, and I/O costs that typically arise when exchanging data between frameworks. The package includes out-of-the-box high-level abstractions for common data types and supports stream pipelining to allow overlapping computation and data transfer.\n\nVineyard runs as a distributed service with a Python client library that connects to a shared-memory manager. It is a CNCF sandbox project and targets scenarios where data is too large for a single machine and multiple systems need to collaborate on preprocessing, analysis, or training tasks. The 16 runtime dependencies include numpy, pandas, pyarrow, and pyyaml, reflecting its role as a bridge between data processing and machine learning ecosystems.","worth_installing":"Yes, if you are building distributed big data pipelines that require zero-copy data sharing across multiple frameworks. The permissive Apache License 2.0 and production-stable status support adoption. However, install only if you have a Vineyard server infrastructure in place and are working at scale; it is not a general-purpose data library for single-machine use. The aging maintenance status warrants monitoring for security updates."},"id":"vineyard","links":{"html":"https://skillfed.io/packages/vineyard","md":"https://skillfed.io/packages/vineyard.md","pypi":"https://pypi.org/project/vineyard/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2024-08-29","license_spdx":null,"license_treatment":"permissive","name":"vineyard","python_support":"unspecified","summary":"An in-memory immutable data manager"},"popularity":{"monthly_downloads":104367,"position":12751,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.24.2"}