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.
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.
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,…
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
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
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
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