1.google-ai-edge / mediapipe
Cross-platform, customizable ML solutions for live and streaming media.
Ranked by Attention Score: stars gained over the last 90 complete days
41 repositories by Attention Score · Aug 5, 2026 – Nov 2, 2026 (UTC)
Cross-platform, customizable ML solutions for live and streaming media.
A high-performance observability data pipeline.
QuestDB is a high performance, open-source, time-series database
A curated list of awesome System Design (A.K.A. Distributed Systems) resources.
Redpanda is a streaming data platform for developers. Kafka API compatible. 10x faster. No ZooKeeper. No JVM!
🌊 Online machine learning in Python
Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
A curated list of awesome big data frameworks, ressources and other awesomeness.
Event streaming platform for agentic AI. Continuously ingest, transform, and serve event streams in real time, at scale.
Upserts, Deletes And Incremental Processing on Big Data.
Building event-driven applications the easy way in Go.
Asynchronous Python framework for event-driven services. A thin client for Kafka, RabbitMQ, NATS, Redis and MQTT with full access to native broker features, plus AsyncAPI docs, in-memory tests and observability out of the box.
Fast, Simple and a cost effective tool to replicate data from Postgres to Data Warehouses, Queues and Storage
Distributed stream processing engine in Rust
Fancy stream processing made operationally mundane
The live data layer for apps and AI agents. Create up-to-the-second views into your business, just using SQL
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》
The fastest unified streaming SQL Engine in a single C++ binary. ⚡ Millisecond latency. 100+ GB/s throughput. Continuously compute stateful context from streams, logs, metrics, events, and CDC.
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.
🦀 event stream processing for developers to collect and transform data in motion to power responsive data intensive applications.
Python Stream Processing
Apache StreamPipes - A self-service (Industrial) IoT toolbox to enable non-technical users to connect, analyze and explore IoT data streams.
Kubernetes-native platform to run massively parallel data/streaming jobs
Python Streaming DataFrames for Kafka
Efficient, easy-to-use, and fast PHP JSON stream parser
A lightweight stream processing library for Go
High-performance time-series aggregation for PostgreSQL
Python Stream Processing
Stream Processing and Complex Event Processing Engine
Low-code tool for automating actions on real time data | Stream processing for the users.
Framework for building Event-Driven Microservices
A compatibility layer for event-driven abstractions
An extensible Java framework for building event-driven applications that break up XML and non-XML data into chunks for data integration
Distributed Stream Processing
Build platforms that flexibly mix SQL, batch, and stream processing paradigms
The database purpose-built for stream processing applications.
A Go port of the Java Streams API. Type-safe and functional Go Streams processing
Distributed Stream and Batch Processing
Lightweight real-time big data streaming engine over Apache Pekko
Daggy - Data Aggregation Utility and C/C++ developer library for data streams catching
Window-Based Hybrid CPU/GPU Stream Processing Engine