We Finally Made Real-Time Data Pipelines Easy

Lean & mean event streaming system to build
AI native pipelines with APIs, edge, sensors, and logs.

Get Started Now

A new EVENT DRIVEN architecture is here

Edge Native
Cloud Native
AI Native

Your modern data stack is BROKEN

Data teams typically manage 5-7 different tools for basic data collection, transformation, and analysis. This leads to high costs, poor performance, and maintenance challenges.

Kafka, Flink, Spark, Airflow, Lambdas - data pipeline spaghetti

You need a SYSTEM not a stack

At InfinyOn we built a complete system for builders, combining the functionality of distributed streaming and stream processing. It's a lean alternative to Kafka, Flink, and microservices.

Accelerate Real-Time AI with Data Streaming

Build complete frameworks for edge-to-core AI data pipelines using event-driven architecture and stream processing.

Edge AI:: Run ML models on the edge.
Continuous Enrichment:: Enrich with Causality and Generative AI.
Observable AI Pipelines:: Monitor model performance, drift, and more.

Accelerate Real-Time AI with Data Streaming

Get Real-Time Insights from Streaming Data

Operate end-to-end real-time data pipelines with advanced stateful stream processing capabilities.

Rust, Python, SQL:: Compose data flows in Rust, Python, and more.
Stateful DataFlow: Build data pipelines with state management built in.
Built in metrics: Monitor and debug complex data flows at ease.

Get Real-Time Insights from Streaming Data

Control Your Data Streaming Stack

Leverage event-driven architecture to ensure data integrity and on-demand access in your streaming applications.

Programmable Connectors:: Get the data you need from any source.
Edge Mirroring:: Prevent edge data loss even with network disruptions.
Delivery Guarantee:: You control delivery semantics and idempotence.

Technology Leaders Experience

By adopting InfinyOn Cloud, we've transformed our engineering velocity and eliminated the roadblocks and delays associated with traditional systems and services, empowering our teams to focus on innovation and growth.

Ben Cleary

CTO of Klarian

Develop. Deploy. Dominate.

Lightweight

Compact 37 Mb binary enables efficient data streaming on edge devices with minimal resources.

Edge to core

Ensure data integrity with our robust edge native stream processing, even in unreliable network conditions.

Run Anywhere

Deploy stream processing workers across distributed networks for flexible data handling.

Composable

Build end-to-end data streaming pipelines with a single, unified framework.

What data practitioners say

Artem

Data Platform Architect

"I would love a unified solution without the memory limitations of JVM based tools."
Joao

Cloud Infrastructure Architect

"It was awesome to see the CLI experience. That's like a million times better than Kafka. I think it's uncomfortable how much better it is than the Kafka."
Jowanza

Data Practitioner, CEO, Author

"The event based approach without babysitting a bunch of point solutions is the way I want to build."

Frequently Asked Questions

: Stream processing allows for real-time data analysis and decision-making. It enables businesses to process and act on data as it’s generated, leading to faster insights, improved operational efficiency, and better user experiences in applications ranging from fraud detection to personalized recommendations.
: InfinyOn exists to simplify event streaming. We firmly believe that event driven architecture and stream processing is the right approach for a connected intelligent digital ecosystem.
: InfinyOn is a lightweight composable streaming system, diverging from existing solutions that cobble together multiple tools and libraries. At the core of InfinyOn is Fluvio distributed streaming engine built from the ground up to be lean, secure, and efficient. InfinyOn includes a complete suite of CLI tools, APIs, and SDKs, to give developers the control and the flexibility to create modular, end-to-end data flows.

Majority of the streaming ecosystem is filled with tools which focus on optimizing existing components—such as enhancing storage speed, file formats, metadata usage, and infrastructure management.

Fluvio takes a fundamentally different approach to build foundational tech. Built from scratch using Rust, it leverages cutting-edge advances in hardware, kernel, and compiler design to ensure superior performance, memory safety, and resource efficiency.

InfinyOn uses WebAssembly for data processing packages to implement nimble, secure, and flexible components. This cohesive design offers developers a unified paradigm for building streaming applications, eliminating the complexity and integration challenges associated with piecing together disparate tools and libraries.
: The components of InfinyOn are:

Fluvio: Open Source Distributed streaming engine or runtime. Over 200k lines of code packaged in a single 37 MB binary. Download with a script, manage using fluvio version manager, deploy on ARM64 edge devices. Cloud native deployment using Kubernetes on InfinyOn Cloud.

Fluvio CLI: Fluvio command line interface or CLI is for users to setup and run Fluvio streaming engine on their terminal.

Fluvio Clients: Rust Client, Python Client, Node Client and additional community clients.

Connector Development Kit(CDK): Fluvio connector development kit is for developers to build connectors to data sources like mqtt, http, s3 etc. as well as data sinks like s3, databases, consumer applications.

Smart Module Development Kit(SMDK): Fluvio smart module development kit is for developers to build smart modules or packages to run unbounded transformations on connectors to collect and distribute data with deduplication, filters, flattening etc. Smart modules are like lambdas to transform streaming data.

Stateful Data Flow(SDF): Stateful data flow is a developer toolkit to build, deploy and maintain end to end stateful streaming data flows on Fluvio. Stateful data flow provides developers with a ruby on rails type experience to express schema, types, state objects, and business logic operators to express chain of stateful and stateless transformation on streaming data.
: There are 3 ways of integrating data sources and sinks with Fluvio.

1. Fluvio Client: Developers use the Fluvio Client to directly integrate Fluvio into live applications. Fluvio client is the most flexible connection to connect with practically any data source or sink.

2. Fluvio Connectors: Fluvio offers pre built connectors which are opinionated fluvio client packages built using Fluvio Connector Development Kit to interact with specific systems like databases, storage layers, messaging protocols, applications.

3. Custom Connectors: Developers can build connectors to any proprietary custom data system using the connector development kit or reach out to us for a custom connector build. We build connectors on demand at extreme speeds. There are some examples in this git repo - https://github.com/fluvio-connectors
: At InfinyOn our goal is to sustainably maintain our open source projects while building a enterprise data platform. InfinyOn is a combination of Fluvio open source and proprietary Stateful DataFlow. We are deliberate about enabling developers to use the open source without worrying about license issues. At the same time we are intentional about making it easy for businesses to make reasonable decisions to adopt commercial licenses whether they want a managed infrastructure platform as a service, or deploy in their own cloud infrastructure. We make it easy for smaller teams to start small without any strings attached.
: Yes. InfinyOn Cloud is a fully managed infrastructure as a service offering of Fluvio and Stateful DataFlow.
: There are 3 main differences between the open source system and InfinyOn Cloud managed service.

1. Cluster Tenancy and Management: As expected InfinyOn Cloud offers additional functionality including multiple users, multiple deployment regions, admin interfaces, secret management, webhook gateway etc.

2. Support, SLAs, P99: Manged InfinyOn Cloud deployments obvious ly get higher priorities on support and performance SLAs. Self hosted installs have optional support add-ons for smaller teams to continue using open source with confidence.

3. Stateful DataFlow Interfaces: InfinyOn Cloud implementation of Stateful DataFlow offers additional UI interfaces and worker management interfaces beyond what the free to use self hosted version provides.
: The technology is certainly capable of supporting custom deployment models. We have built InfinyOn Cloud with a secure by design approach. There is a clear separation of control plane and data plane and complete security and privacy for your data on fully managed InfinyOn Cloud. You can deploy in the region of your choice.

Air gapped installs and BYOC installs are only entertained in enterprise contracts.

Company

Resources

We Finally Made Real-Time Data Pipelines Easy

A new EVENT DRIVEN architecture is here

Edge Native

Cloud Native

AI Native

Your modern data stack is BROKEN

You need a SYSTEM not a stack

Accelerate Real-Time AI with Data Streaming

Get Real-Time Insights from Streaming Data

Control Your Data Streaming Stack

Technology Leaders Experience

Develop. Deploy. Dominate.

What data practitioners say

Artem

Data Platform Architect

Joao

Cloud Infrastructure Architect

Jowanza

Data Practitioner, CEO, Author

Launch in minutes. Scale to infinity.

Frequently Asked Questions