Showing 7 open source projects for "fast linux"

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  • 1
    collapse

    collapse

    Advanced and Fast Data Transformation in R

    collapse is a high-performance R package designed for fast and efficient data transformation, aggregation, reshaping, and statistical computation. Built to offer a more performant alternative to dplyr and data.table, it is particularly well-suited for large datasets and econometric applications. It operates on base R data structures like data frames and vectors and uses highly optimized C++ code under the hood to deliver significant speed improvements. collapse also includes tools for...
    Downloads: 0 This Week
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  • 2
    fluentbit

    fluentbit

    Fast and Lightweight Logs and Metrics processor for Linux, BSD, OSX

    Fluent Bit is a super-fast, lightweight, and highly scalable logging and metrics processor and forwarder. It is the preferred choice for cloud and containerized environments. A robust, lightweight, and portable architecture for high throughput with low CPU and memory usage from any data source to any destination. Proven across distributed cloud and container environments. Highly available with I/O handlers to store data for disaster recovery. Granular management of data parsing and routing....
    Downloads: 2 This Week
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  • 3
    CocoIndex

    CocoIndex

    ETL framework to index data for AI, such as RAG

    CocoIndex is an open-source framework designed for building powerful, local-first semantic search systems. It lets users index and retrieve content based on meaning rather than keywords, making it ideal for modern AI-based search applications. CocoIndex leverages vector embeddings and integrates with various models and frameworks, including OpenAI and Hugging Face, to provide high-quality semantic understanding. It’s built for transparency, ease of use, and local control over your search...
    Downloads: 8 This Week
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  • 4
    Watermill

    Watermill

    Building event-driven applications the easy way in Go

    Go library for building event-driven applications. Our goal was to create a tool that is easy to understand, even by junior developers. It doesn't matter if you want to do Event-driven architecture, CQRS, Event Sourcing or just stream MySQL Binlog to Kafka. Watermill was designed to process hundreds of thousands of messages per second. Every component is built in a way that allows you to configure it for your needs. You can also implement your own middleware for the router. Watermill is...
    Downloads: 7 This Week
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  • 5
    protoactor-go

    protoactor-go

    Proto Actor - Ultra fast distributed actors for Go, C# and Java/Kotlin

    Built on cloud-native technologies. Taking advantage of proven stability and performance. Asynchronous and Distributed by design. High-level abstractions like Actors and Virtual Grains. Capable of millions of messages per second cross-process communication. Write systems that self-heal using supervisor hierarchies. The Actor Model provides a higher level of abstraction for writing concurrent and distributed systems. It alleviates the developer from having to deal with explicit locking and...
    Downloads: 3 This Week
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  • 6
    text-dedup

    text-dedup

    All-in-one text de-duplication

    text-dedup is a Python library that enables efficient deduplication of large text corpora by using MinHash and other probabilistic techniques to detect near-duplicate content. This is especially useful for NLP tasks where duplicated training data can skew model performance. text-dedup scales to billions of documents and offers tools for chunking, hashing, and comparing text efficiently with low memory usage. It supports Jaccard similarity thresholding, parallel execution, and flexible...
    Downloads: 0 This Week
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  • 7
    Wally

    Wally

    Distributed Stream Processing

    Wally is a fast-stream-processing framework. Wally makes it easy to react to data in real-time. By eliminating infrastructure complexity, going from prototype to production has never been simpler. When we set out to build Wally, we had several high-level goals in mind. Create a dependable and resilient distributed computing framework. Take care of the complexities of distributed computing "plumbing," allowing developers to focus on their business logic. Provide high-performance & low-latency...
    Downloads: 6 This Week
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