Columnar In-Memory डेटा फॉर्मेट्स
एनालिटिकल प्रोसेसिंग टूल्स और सिस्टम्स में स्ट्रक्चर्ड डेटा शेयर करने के लिए हाई-परफॉरमेंस ओपन-सोर्स लाइब्रेरीज़ और स्पेसिफिकेशन्स।
Columnar In-Memory डेटा फॉर्मेट्स
AI के साथ बेहतरीन रिपॉजिटरी खोजें।हम AI का उपयोग करके सबसे सटीक रिपॉजिटरी खोजेंगे।
- apache/arrow
apache/arrow
16,529GitHub पर देखेंArrow 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
Apache Arrow is the canonical open‑source columnar in‑memory format that provides a standardized, language‑agnostic columnar layout with zero‑copy sharing and wide multi‑language support, exactly matching the need for efficient data interchange across tools and languages.
C++Columnar FormatsIn-Process AnalyticsLanguage Interoperability - wesm/feather
wesm/feather
2,757GitHub पर देखेंFeather: fast, interoperable binary data frame storage for Python, R, and more powered by Apache Arrow
Feather is a columnar binary data format built on Apache Arrow, purpose-built for fast, zero-copy data interchange between Python, R, and other languages, exactly matching the need for an efficient, open-source columnar in-memory format for cross-language sharing.
JavaScriptData Formats
