InfinyOn provides a lightweight, composable event streaming platform that enables the rapid construction of stateful data pipelines using APIs, edge devices, and various data sources. This system addresses the inefficiencies of managing multiple tools for data collection and processing, allowing teams to achieve real-time insights and maintain data integrity across distributed environments.
Funding
$5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
FVFounders
Product
Problem
Data teams often struggle with the complexity of managing multiple disparate tools for data collection, transformation, and analysis, leading to increased costs, reduced performance, and significant maintenance overhead. Existing solutions often require cobbling together various tools and libraries, creating integration challenges and hindering real-time insights.
Solution
InfinyOn provides a lightweight, composable event streaming platform designed to simplify the construction of stateful data pipelines. This system combines the functionality of distributed streaming and stream processing into a single, unified framework, offering a lean alternative to Kafka, Flink, and microservices. By leveraging event-driven architecture, InfinyOn ensures data integrity and on-demand access, enabling teams to build AI-native pipelines with APIs, edge devices, sensors, and logs. The platform supports real-time data analysis and decision-making, allowing businesses to process and act on data as it’s generated.
Target Audience
The primary audience includes data platform architects, cloud infrastructure architects, data practitioners, and technology leaders seeking to streamline their data streaming infrastructure and accelerate real-time AI initiatives.
Features
- Lightweight and compact (37MB binary) for efficient data streaming on edge devices
- Edge-native stream processing to ensure data integrity, even in unreliable network conditions
- Support for Rust, Python, and SQL for composing data flows
- Built-in state management for building stateful data pipelines
- Programmable connectors for integrating data from any source
- Edge mirroring to prevent data loss during network disruptions
- Delivery guarantee with control over delivery semantics and idempotence
- Integration with Fluvio, an open-source distributed streaming engine
- Connector Development Kit (CDK) for building custom connectors to data sources and sinks
- Smart Module Development Kit (SMDK) for building data transformation packages
- Stateful Data Flow (SDF) toolkit for building, deploying, and maintaining end-to-end stateful streaming data flows