Stream Processing
Showing 36 of 268 projects
A distributed stream processing system written in Haskell that guarantees exactly-once semantics.
A probabilistic data structure service and storage for efficient frequency, cardinality, and membership queries on large datasets.
A reactive Kafka client for Vert.x that provides asynchronous consumer and producer APIs with stream support.
A Go library implementing IO, Stream, and Fiber monads with generics, inspired by cats-effect and fs2.
Apply SQL queries and spatial filters to GeoJSON data in memory, with support for streams and Esri format conversion.
An end-to-end data management system for IoT, optimizing stream processing across cloud, edge, and sensor deployments.
A TypeScript/JavaScript library providing Python-inspired iteration utilities for working with iterables, streams, and pipes.
A comprehensive Ada utility library providing logging, serialization, encoding, stream composition, and concurrency tools for building robust applications.
F# library for serializing events in event-sourcing systems with version-tolerant converters for System.Text.Json and Newtonsoft.Json.
A high-performance C++ JSON library with a binary wire protocol, optimized for network efficiency and zero-copy parsing.
A fast Node.js stream splitter for binary data that splits on newlines or custom delimiters without converting to strings.
A Node.js Transform stream that processes data chunks concurrently with configurable max concurrency.
A multi-core stream processing engine for high-throughput window aggregation with optional exactly-once fault tolerance.
OCaml bindings for Apache Kafka, enabling Kafka client functionality in OCaml applications.
Go implementation of Count-Min-Log sketch for improved approximate counting of low-frequency events.
A thin wrapper around through2 that provides an Array.prototype.map-like API for transforming Node.js streams.
A runtime supervisor for deploying and running data processing programs called Sequences on Linux servers, Docker, and Kubernetes clusters.
A multi-threaded Python example demonstrating how to produce and consume records from Amazon Kinesis streams.
A fluent builder for lazy streams and generators in Groovy, enabling functional-style data processing.
A utilities library for Reactive Streams in the JDK, providing familiar operators like map and filter for java.util.concurrent.Flow.
A Node.js library that pipes queued streams sequentially to preserve content order.
A .NET interface to the Amazon Kinesis Client Library MultiLangDaemon for building distributed streaming data applications.
A Go package providing a simplistic implementation of pipelines using goroutines for concurrent data processing.
A lightweight SQL-based stream processing engine for IoT edge, enabling real-time data transformation and windowed aggregation.
A Ruby gem for extracting data from JSON streams based on keys, nesting levels, or custom conditions without implementing low-level callbacks.
A simple, Kafka-inspired stream processing library for Scala with exactly-once semantics and strong ordering guarantees.
A Node.js transform stream that inspects the first chunk of data before choosing a parsing strategy.
Object Pascal library for encoding and decoding multiple base formats including Base16, Base32, Base58, Base64, and Base85.
A fixed-length blocking queue implemented as a GenServer in Elixir for producer-consumer coordination.
A text stream monitoring library that detects keywords, phrases, regexes, and complex Lucene queries in documents.
A generalized map-reduce library for parallel processing on multicore systems, handling large files and infinite streams.
A fast, stream-based XML Sitemap generator for Elixir with low memory consumption.
A fully embeddable data streaming engine and stream processing API for Java, designed as an alternative to Kafka.
A ClojureScript port of the Manifold library for asynchronous programming with streams and deferred values.
A Crystal library providing modern concurrency tools like parallel enumerables, channels, and synchronization primitives.
A window-based hybrid stream processing engine that leverages both CPU and GPU resources for high-performance data analytics.
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