Showing 74 open source projects for "stream"

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  • 1
    YAO

    YAO

    Yao A low code engine to create web services and dashboard

    ...Yao is a low-code engine that creates a database model, writes API services, and describes dashboard interface just by JSON for web & hardware, no code, and 10x productivity. Yao is based on the flow-based programming idea, developed in the Go language, and supports multiple ways to expand the data stream processor. This makes Yao extremely versatile, which can replace programming languages ​​in most scenarios, and is 10 times more efficient than traditional programming languages ​​in terms of reusability and coding efficiency; application performance and resource ratio Better than PHP, JAVA and other languages. Yao has a built-in data management system. ...
    Downloads: 0 This Week
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  • 2
    Semantic Type Detection

    Semantic Type Detection

    Metadata/data identification Java library

    ...Broad country/language support - including US, Canada, Mexico, Brazil, UK, Australia, much of Europe, Japan and China. Support for sharded analysis (i.e. Analysis results can be merged) Once stream is profiled then subsequent samples can be validated and/or new samples can be generated.
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  • 3
    HStreamDB

    HStreamDB

    HStreamDB is an open-source, cloud-native streaming database

    HStreamDB is an open-source, cloud-native streaming database for IoT and beyond. Modernize your data stack for real-time applications. By subscribing to streams in HStreamDB, any update of the data stream will be pushed to your apps in real-time, and this promotes your apps to be more responsive. You can also replace message brokers with HStreamDB and everything you do with message brokers can be done better with HStreamDB. HStreamDB provides built-in support for event time-based stream processing. You can use your familiar SQL to perform basic filtering and transformation operations, statistics and aggregation based on multiple kinds of time windows and even joining between multiple streams. ...
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  • 4
    memphis

    memphis

    Next-Generation Event Processing Platform

    ...Provide great performance while maintaining efficient resource consumption. Increase observability, integrations with 3rd-party monitoring tools, real-time notifications, stream lineage, and therefore troubleshooting time reduction. Enable rapid development and ultra-short time-to-production.
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  • 5
    Tokenize.jl

    Tokenize.jl

    Tokenization for Julia source code

    Tokenize is a Julia package that serves a similar purpose and API as the tokenize module in Python but for Julia. This is to take a string or buffer containing Julia code, perform lexical analysis and return a stream of tokens.
    Downloads: 0 This Week
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  • 6
    Fondant

    Fondant

    Production-ready data processing made easy and shareable

    Fondant is a modular, pipeline-based framework designed to simplify the preparation of large-scale datasets for training machine learning models, especially foundation models. It offers an end-to-end system for ingesting raw data, applying transformations, filtering, and formatting outputs—all while remaining scalable and traceable. Fondant is designed with reproducibility in mind and supports containerized steps using Docker, making it easy to share and reuse data processing components....
    Downloads: 0 This Week
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  • 7
    MOA - Massive Online Analysis

    MOA - Massive Online Analysis

    Big Data Stream Analytics Framework.

    A framework for learning from a continuous supply of examples, a data stream. Includes classification, regression, clustering, outlier detection and recommender systems. Related to the WEKA project, also written in Java, while scaling to adaptive large scale machine learning.
    Downloads: 29 This Week
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  • 8
    protoactor-go

    protoactor-go

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

    ...Grain abstraction, which provides a straightforward approach to building distributed interactive applications, without the need to learn complex programming patterns for handling concurrency, fault tolerance, and resource management. This allows Proto.Actor to leverage in-process performance for realtime stream processing.
    Downloads: 0 This Week
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  • 9
    An innovative Open Source CEP (Complex Event Processing) engine. It implements the event stream processing as a library embeddable in C++ and Perl. You can think of the Complex Event Processing engine as an in-memory database driven by triggers, or a data-flow machine, or a spreadsheet on steroids (and without the GUI part).
    Downloads: 0 This Week
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  • 10
    Strings Edit

    Strings Edit

    String editing and formatting library for Ada

    Strings edit is a library that provides I/O facilities for integers, floating-point numbers, Roman numerals, and strings. Both input and output subroutines support string pointers for consequent stream processing. The output can be aligned in a fixed size field with padding. Numeric input can be checked against expected values range to be either saturated or to raise an exception. For floating-point output either relative or absolute output precision can be specified. UTF-8 encoded strings are supported, including wildcard pattern matching, sets and maps of code points, upper/lowercase, and other Unicode categorizations.
    Downloads: 0 This Week
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  • 11
    Ethereum ETL

    Ethereum ETL

    Python scripts for ETL (extract, transform and load) jobs for Ethereum

    Python scripts for ETL (extract, transform and load) jobs for Ethereum blocks, transactions, ERC20 / ERC721 tokens, transfers, receipts, logs, contracts, internal transactions. Data is available in Google BigQuery. Ethereum ETL lets you convert blockchain data into convenient formats like CSVs and relational databases.
    Downloads: 0 This Week
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  • 12
    data-diff

    data-diff

    Efficiently diff rows across two different databases

    ...Since copying entire datasets in batch is often infeasible at the modern data scale, businesses rely on the Change Data Capture (CDC) approach of replicating data using a continuous stream of updates.
    Downloads: 0 This Week
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  • 13
    VirtualGL

    VirtualGL

    3D Without Boundaries

    VirtualGL redirects 3D commands from a Unix/Linux OpenGL application onto a server-side GPU and converts the rendered 3D images into a video stream with which remote clients can interact to view and control the 3D application in real time.
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    Downloads: 63,844 This Week
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  • 14
    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...
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  • 15
    Amazon Kinesis Flink Connectors

    Amazon Kinesis Flink Connectors

    Contains various Apache Flink connectors to connect to AWS data

    This library contains various Apache Flink connectors to connect to AWS data sources and sinks. This repository contains various Apache Flink connectors to connect to AWS Kinesis data sources and sinks. Flink maintain backwards compatibility for the Sink interface used by the Firehose Producer. This project is compatible with Flink 1.x, there is no guarantee it will support Flink 2.x should it release in the future. An Apache Flink application is a Java or Scala application that is created...
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  • 16
    SnappyData

    SnappyData

    Memory optimized analytics database, based on Apache Spark

    ...By fusing an in-memory hybrid database inside Apache Spark, it provides analytic query processing, mutability/transactions, access to virtually all big data sources and stream processing all in one unified cluster. One common use case for SnappyData is to provide analytics at interactive speeds over large volumes of data with minimal or no pre-processing of the dataset. For instance, there is no need to often pre-aggregate/reduce or generate cubes over your large data sets for ad-hoc visual analytics. ...
    Downloads: 0 This Week
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  • 17
    Padasip

    Padasip

    Python Adaptive Signal Processing

    Padasip (Python Adaptive Signal Processing) is a Python library tailored for adaptive filtering and online learning applications, particularly in signal processing and time series forecasting. It includes a variety of adaptive filter algorithms such as LMS, RLS, and their variants, offering real-time adaptation to changing environments. The library is lightweight, well-documented, and ideal for research, prototyping, or teaching purposes. Padasip supports both supervised and unsupervised...
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  • 18
    Javis

    Javis

    Julia Animations and Visualizations

    ...Javis makes generating simple animations a breeze! Want to learn more? Check out our documentation for tutorials, our contributing guidelines, and the mission of Javis.jl. We have a live Zulip stream that you can join to discuss Javis with other Javis users.
    Downloads: 0 This Week
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  • 19
    Amadeus

    Amadeus

    Harmonious distributed data analysis in Rust

    Amadeus is a high-performance, distributed data processing framework written in Rust, designed to offer an ergonomic and safe alternative to tools like Apache Spark. It provides both streaming and batch capabilities, allowing users to work with real-time and historical data at scale. Thanks to Rust’s memory safety and zero-cost abstractions, Amadeus delivers performance gains while reducing the complexity and bugs common in large-scale data pipelines. It emphasizes developer productivity...
    Downloads: 2 This Week
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  • 20
    FLOGO

    FLOGO

    Simplify building efficient & modern serverless functions and apps

    ...A simple pipeline-based stream processing action with event joining capabilities across multiple triggers & aggregation over time windows. Microgateway pattern for conditional, content-based routing, JWT validation, rate limiting, circuit breaking and other common patterns.
    Downloads: 0 This Week
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  • 21
    ksqlDB

    ksqlDB

    The database purpose-built for stream processing applications

    ...Three categories are foundational to building an application: collections, stream processing, and queries. Streams are immutable, append-only sequences of events. They're useful for representing a series of historical facts. Tables are mutable collections of events. They let you represent the latest version of each value per key.
    Downloads: 0 This Week
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  • 22
    TensorWatch

    TensorWatch

    Debugging, monitoring and visualization for Python Machine Learning

    TensorWatch is an open source debugging and visualization platform created by Microsoft Research to support machine learning, deep learning, and reinforcement learning workflows. It enables developers to observe training behavior in real time through interactive visualizations, primarily within Jupyter Notebook environments. The tool treats most data interactions as streams, allowing flexible routing, storage, and visualization of metrics generated during model training. A distinctive...
    Downloads: 0 This Week
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  • 23
    DSPatch

    DSPatch

    The Refreshingly Simple C++ Dataflow Framework

    Webite: http://flowbasedprogramming.com DSPatch, pronounced "dispatch", is a powerful C++ dataflow framework. DSPatch is not limited to any particular domain or data type, from reactive programming to stream processing, DSPatch's generic, object-oriented API allows you to create virtually any dataflow system imaginable. *See also:* DSPatcher ( https://github.com/MarcusTomlinson/DSPatcher ): A cross-platform graphical tool for building DSPatch circuits. DSPatchables ( https://github.com/MarcusTomlinson/DSPatchables ): A DSPatch component repository.
    Downloads: 0 This Week
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  • 24
    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.
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  • 25
    Cosmos DB Spark

    Cosmos DB Spark

    Apache Spark Connector for Azure Cosmos DB

    ...The connector allows you to easily read to and write from Azure Cosmos DB via Apache Spark DataFrames in Python and Scala. It also allows you to easily create a lambda architecture for batch-processing, stream-processing, and a serving layer while being globally replicated and minimizing the latency involved in working with big data.
    Downloads: 0 This Week
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