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2 Repos

Awesome GitHub RepositoriesHigh-Performance Containers

Optimized data structures designed for extreme throughput and efficient memory access patterns.

Distinct from High-Performance Data Infrastructures: Existing candidates are for specific domains (game emulators, JSON parsers, infrastructure) rather than general-purpose container libraries.

Explore 2 awesome GitHub repositories matching data & databases · High-Performance Containers. Refine with filters or upvote what's useful.

Awesome High-Performance Containers GitHub Repositories

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  • abseil/abseil-cppAvatar von abseil

    abseil/abseil-cpp

    17,334Auf GitHub ansehen↗

    Abseil is a common utility library for C++ that provides foundational building blocks for applications. It serves as a collection of optimized utility functions and data structures that augment the C++ standard library across different compiler versions. The library is distinguished by its high-performance containers, including SIMD-accelerated hash maps and sets for efficient key-value lookups. It also provides a comprehensive framework for computing absolute time points, durations, and timestamps across global time zones. The project covers a broad range of capability areas, including conc

    Ships SIMD-accelerated hash maps and sets for high-performance key-value lookups and storage.

    C++
    Auf GitHub ansehen↗17,334
  • msgspec/msgspecAvatar von msgspec

    msgspec/msgspec

    3,821Auf GitHub ansehen↗

    msgspec is a high-performance data modeling, serialization, and schema validation toolkit for Python. It serves as a type-safe serialization framework that integrates schema enforcement and data parsing into a single pass, functioning as both a data serialization library and a schema validation system based on standard Python type annotations. The project distinguishes itself through high-performance structural primitives, including compilation-based routine generation and zero-copy buffer parsing. It optimizes memory usage via garbage collection-aware layouts and reduces processing overhead

    Provides optimized data containers with faster instantiation and lower memory overhead than standard dataclasses.

    Pythondeserializationjsonjson-schema
    Auf GitHub ansehen↗3,821
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