Stream Processing Collection

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🔮Psychic

★★★★

“Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.”

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🔥Fire

★★★★

“Cross-platform, customizable ML solutions for live and streaming media.”

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⚙️Steel

★★★★

“A high-performance observability data pipeline.”

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⚡Thunder

★★★

“flink learning blog. http://www.54tianzhisheng.cn/ 含 Flink 入门、概念、原理、实战、性能调优、源码解析等内容。涉及 Flink Connector、Metrics、Library、DataStream API、Table API & SQL 等内容的学习案例，还有 Flink 落地应用的大型项目案例（PVUV、日志存储、百亿数据实时去重、监控告警）分享。欢迎大家支持我的专栏《大数据实时计算引擎 Flink 实战与性能优化》”

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📦Normal

★★★

“A curated list of awesome big data frameworks, ressources and other awesomeness.”

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🔥Fire

★★★

“Redpanda is a streaming data platform for developers. Kafka API compatible. 10x faster. No ZooKeeper. No JVM!”

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📦Normal

★★★

“A curated list of awesome System Design (A.K.A. Distributed Systems) resources. ”

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🌊Water

★★★

“Building event-driven applications the easy way in Go.”

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⚙️Steel

★★★

“Event streaming platform for agentic AI. Continuously ingest, transform, and serve event streams in real time, at scale.”

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🌊Water

★★★

“Fancy stream processing made operationally mundane”

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⚔️Fighting

★★★

“Fast and Lightweight Logs, Metrics and Traces processor for Linux, BSD, OSX and Windows”

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🔮Psychic

★★★

“Python Stream Processing”

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⚡Thunder

★★★

“Hazelcast is a unified real-time data platform combining stream processing with a fast data store, allowing customers to act instantly on data-in-motion for real-time insights.”

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⚙️Steel

★★★

“The live data layer for apps and AI agents. Create up-to-the-second views into your business, just using SQL”

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⚡Thunder

★★★

“Upserts, Deletes And Incremental Processing on Big Data.”

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🔮Psychic

★★★

“🌊 Online machine learning in Python”

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🔮Psychic

★★★

“FastStream is an asynchronous Python framework for building event-driven applications. It brings together message broker integration, dependency injection, validation, testing utilities, and AsyncAPI documentation generation in a single toolkit”

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⚙️Steel

★★★

“🦀 event stream processing for developers to collect and transform data in motion to power responsive data intensive applications.”