Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
- batch-processing
- kafka
- pathway
- python
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Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.
Apache Spark - A unified analytics engine for large-scale data processing
All-in-one IoT Platform - Device management, data collection, processing and visualization.
SubQuery is an Open, Flexible, Fast and Universal data indexing framework for web3. Our mission is to help developers create the decentralised products of the future.
The Open Context Layer for Data and AI , OpenMetadata is the open platform for building trusted data context and business semantics for humans, AI assistants, and agents.
Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.
Logstash - transport and process your logs, events, or other data
Incremental engine for long horizon agents 🌟 Star if you like it!
Building event-driven applications the easy way in Go.
SeaTunnel is a multimodal, high-performance, distributed, massive data integration tool.
Event streaming platform for agentic AI. Continuously ingest, transform, and serve event streams in real time, at scale.
Fancy stream processing made operationally mundane
Distributed and fault-tolerant realtime computation: stream processing, continuous computation, distributed RPC, and more
Apache Beam is a unified programming model for Batch and Streaming data processing.
[SIGMOD'27] Easy Data Preparation with latest LLMs-based Operators and Pipelines.
Fast and Lightweight Logs, Metrics and Traces processor for Linux, BSD, OSX and Windows
Data processing for and with foundation models! 🍎 🍋 🌽 ➡️ ➡️🍸 🍹 🍷
deepstream.io server
Python Stream Processing
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.
The live data layer for apps and AI agents. Create up-to-the-second views into your business, just using SQL
Upserts, Deletes And Incremental Processing on Big Data.
🦀 event stream processing for developers to collect and transform data in motion to power responsive data intensive applications.
Distributed stream processing engine in Rust