awesome-repositories.com
Blog
awesome-repositories.com

Descoperă cele mai bune repository-uri open source cu căutare AI.

ExploreazăCăutări recomandateAlternative open-sourceSoftware self-hostedBlogHartă site
ProiectDespreCum realizăm clasamentulPresăServer MCP
LegalConfidențialitateTermeni
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·
OpenHFT avatar

OpenHFT/Chronicle-Queue

0
View on GitHub↗
3,692 stele·562 fork-uri·Java·apache-2.0·2 vizualizărichronicle.software/products/chronicle-queue↗

Chronicle Queue

Chronicle Queue is a high-performance data handling system featuring off-heap message queues, memory-mapped file stores, and replicated message stores. It provides a binary compatible memory layout that enables different programming languages to share data without serialization overhead.

The system utilizes a replicated message store to synchronize data across multiple nodes, ensuring high availability and instant failover. Its memory-mapped architecture supports deterministic replay from disk and low-latency data recording.

The project implements off-heap memory management and zero-allocation processing to eliminate garbage collection pauses and system jitter. It covers capability areas including inter-process communication, append-only sequential logging, and deterministic event sourcing.

Features

  • Memory-Mapped File Access - Provides a persistence engine that maps disk files directly into process memory for low-latency recording and replay.
  • Memory Layouts - Defines a strict binary memory layout that allows multiple programming languages to read shared data without translation.
  • Memory-Mapped Storage - Uses memory-mapped files to map disk storage directly into the process address space for low-latency persistence.
  • Shared Memory Data Exchange - Provides high-performance data transfer between processes using binary compatible shared memory buffers to eliminate serialization overhead.
  • Off-Heap Queues - Ships a high-performance binary queue that stores data off-heap to eliminate Java garbage collection pauses.
  • Append-Only Log Storage - Implements an immutable, chronological log structure to maximize disk throughput and ensure deterministic data replay.
  • Low Latency Messaging - Implements low-latency messaging by utilizing off-heap memory to bypass garbage collection delays.
  • Inter-Process Communication - Facilitates high-performance inter-process communication using shared memory primitives and binary compatible layouts.
  • Off-Heap Memory Managers - Manages data outside the managed heap to eliminate garbage collection pauses and reduce system jitter.
  • Zero-Allocation Architectures - Employs a zero-allocation architecture and off-heap memory to completely eliminate garbage collection pauses.
  • Local Message Loggers - Maintains a local binary log of messages on disk to ensure recovery and deterministic replay after crashes.
  • Event Sourcing Engines - Implements deterministic event sourcing by recording message sequences to disk for exact system state replay.
  • Queue High Availability - Ensures high availability and failover by replicating queue data across multiple network nodes.
  • High-Frequency Trading Infrastructure - Provides the high-performance, nanosecond-precision infrastructure required for reliable financial trading and tick data persistence.
  • Shared Memory Management - Employs shared memory management with atomic operations and memory barriers for lock-free concurrency across processes.
  • Zero-Allocation Buffer Encoders - Provides serialization mechanisms that write directly to buffers to avoid creating temporary objects during processing.
  • Data Structures and Memory - Micro second messaging that stores everything to disk.
  • Collection Libraries - Low-latency messaging library with disk-based persistence.

Istoric stele

Graficul istoricului de stele pentru openhft/chronicle-queueGraficul istoricului de stele pentru openhft/chronicle-queue

Căutare AI

Explorează mai multe repository-uri excelente

Descrie ce ai nevoie în limbaj simplu — AI-ul sortează mii de proiecte open source selectate în funcție de relevanță.

Start searching with AI

Întrebări frecvente

Ce face openhft/chronicle-queue?

Chronicle Queue is a high-performance data handling system featuring off-heap message queues, memory-mapped file stores, and replicated message stores. It provides a binary compatible memory layout that enables different programming languages to share data without serialization overhead.

Care sunt principalele funcționalități ale openhft/chronicle-queue?

Principalele funcționalități ale openhft/chronicle-queue sunt: Memory-Mapped File Access, Memory Layouts, Memory-Mapped Storage, Shared Memory Data Exchange, Off-Heap Queues, Append-Only Log Storage, Low Latency Messaging, Inter-Process Communication.

Care sunt câteva alternative open-source pentru openhft/chronicle-queue?

Alternativele open-source pentru openhft/chronicle-queue includ: gunnarmorling/1brc — The 1BRC (One Billion Row Challenge) is a Java performance benchmarking exercise that processes one billion… vaexio/vaex — Vaex is a high-performance Apache Arrow DataFrame library and out-of-core data processing engine designed to handle… boltdb/bolt — Bolt is a single-file embedded key-value store for Go applications. It is an ACID transactional database that… dora-rs/dora — Dora is a robotics dataflow framework and distributed orchestrator used to build and manage processing pipelines. It… cch123/golang-notes — This project is a technical reference and a collection of internal analysis notes focused on the Go language runtime… morvanzhou/tutorials — This repository is a comprehensive collection of instructional guides and practical examples for Python development,…

Alternative open-source pentru Chronicle Queue

Proiecte open-source similare, clasificate după numărul de funcționalități comune cu Chronicle Queue.
  • gunnarmorling/1brcAvatar gunnarmorling

    gunnarmorling/1brc

    8,062Vezi pe GitHub↗

    The 1BRC (One Billion Row Challenge) is a Java performance benchmarking exercise that processes one billion temperature records from a text file to compute the minimum, mean, and maximum temperature per weather station. At its core, it is a large-scale data aggregation challenge designed to test how efficiently a Java program can parse and aggregate structured data from a plain text file, serving as both a programming exercise and a benchmark for Java performance optimization. The project distinguishes itself through a collection of performance-oriented architectural patterns for high-through

    Java1brcchallenges
    Vezi pe GitHub↗8,062
  • vaexio/vaexAvatar vaexio

    vaexio/vaex

    8,506Vezi pe GitHub↗

    Vaex is a high-performance Apache Arrow DataFrame library and out-of-core data processing engine designed to handle billion-row tabular datasets in Python. It functions as a lazy evaluation framework that defers computations and transformations until results are required, enabling the processing of datasets that exceed available system RAM by mapping files directly from disk. The project distinguishes itself as a tool for big data visualization and exploration, specifically integrated for use within interactive notebooks. It provides specialized capabilities for machine learning feature engin

    Python
    Vezi pe GitHub↗8,506
  • boltdb/boltAvatar boltdb

    boltdb/bolt

    14,642Vezi pe GitHub↗

    Bolt is a single-file embedded key-value store for Go applications. It is an ACID transactional database that organizes data in B+trees on disk to provide efficient sorted key retrieval and range scans. The system uses a memory-mapped model to map the database file directly into the process address space for fast random-access reads. The project distinguishes itself through a multi-version concurrency control architecture that allows multiple simultaneous readers to access a consistent snapshot of data without blocking a writer. It employs a single-writer multi-reader locking model and uses a

    Go
    Vezi pe GitHub↗14,642
  • dora-rs/doraAvatar dora-rs

    dora-rs/dora

    2,929Vezi pe GitHub↗

    Dora is a robotics dataflow framework and distributed orchestrator used to build and manage processing pipelines. It enables the deployment of robotics workloads across clusters with remote node execution and provides a real-time data pipeline for predictable performance. The system is distinguished by its support for multi-language nodes written in Rust, Python, C, or C++ that interoperate within a single dataflow. It utilizes a zero-copy shared-memory transport and columnar formats to minimize latency for large payloads, and it includes bidirectional bridges to integrate with external ecosy

    Rustdataflowembodied-ailow-latency
    Vezi pe GitHub↗2,929
  • Vezi toate cele 30 alternative pentru Chronicle Queue→