Building event-driven applications the easy way in Go.
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- event-driven
- event-sourcing
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Building event-driven applications the easy way in Go.
Fancy stream processing made operationally mundane
The Reactive Extensions for .NET
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
🦀 event stream processing for developers to collect and transform data in motion to power responsive data intensive applications.
Concurrent and multi-stage data ingestion and data processing with Elixir
High-performance time-series aggregation for PostgreSQL
Project Flogo is an open source ecosystem of opinionated event-driven capabilities to simplify building efficient & modern serverless functions, microservices & edge apps.
Compositional, streaming I/O library for Scala
Python Streaming DataFrames for Kafka
A platform that makes it easy for developers to build realtime, cost-effective, operations-focused applications
High performance Rust stream processing engine seamlessly integrates AI capabilities, providing powerful real-time data processing and intelligent analysis.
A compatibility layer for event-driven abstractions
🌊 Continuously synchronize the systems where your data lives, to the systems where you _want_ it to live, by managing your data flows with Estuary. 🌊
Tenzir is the data pipeline engine for security teams.
Low-code tool for automating actions on real time data | Stream processing for the users.
HStreamDB is an open-source, cloud-native streaming database for IoT and beyond. Modernize your data stack for real-time applications.
🏎️ Streams & Reactive Programming paradigm for Go: declarative and composable API for event-driven applications
Conduit streams data between data stores. Kafka Connect replacement. No JVM required.
Compositional pipelines
Streaming reactive and dataflow graphs in Python
Series and Panels for Real-time and Exploratory Analysis of Data Streams
A stream processing framework to build stateless applications on Kafka