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.
A realtime distributed messaging platform
Open-source data movement for ELT pipelines and AI agents — from APIs, databases & files to warehouses, lakes, and AI applications. Both self-hosted and Cloud.
High-Performance server for NATS.io, the cloud and edge native messaging system.
IM Chat OpenClaw
Open source RabbitMQ: core server and tier 1 (built-in) plugins
Open-Source Web UI for Apache Kafka Management
Diskless Kafka® on S3. 10x Cost-Effective. No Cross-AZ Traffic Cost. Autoscale in seconds. Single-digit ms latency. Multi-AZ Availability.
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
Build, Manage and Deploy AI/ML Systems
Event streaming platform for agentic AI. Continuously ingest, transform, and serve event streams in real time, at scale.
Efficient reliable UDP unicast, UDP multicast, and IPC message transport
[SIGMOD'27] Easy Data Preparation with latest LLMs-based Operators and Pipelines.
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.
Migrate to PostgreSQL in a single command!
The live data layer for apps and AI agents. Create up-to-the-second views into your business, just using SQL
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.
🦀 event stream processing for developers to collect and transform data in motion to power responsive data intensive applications.
Distributed stream processing engine in Rust
ingestr is a CLI tool to copy data between any databases with a single command seamlessly.
Fast, efficient, and scalable distributed map/reduce system, DAG execution, in memory or on disk, written in pure Go, runs standalone or distributedly.
Fast, Simple and a cost effective tool to replicate data from Postgres to Data Warehouses, Queues and Storage
A modern high-performance open source message queuing system