IoT

Stream Processing Where No One Else Can

Bytewax is the ideal solution for processing IoT data streams in complex air-gapped or edge environments with low footprint requirements and network connectivity issues like ships, power plants, and satellites.

Use Cases from Our Community

Stream Processing for the Most Challenging Environments

With minimal infrastructure requirements, Bytewax ensures robust, efficient stream processing is accessible everywhere, revolutionizing how IoT deployments leverage real-time data under any conditions.

DSP

Digital Signal Processing

Bytewax facilitates real-time digital signal processing both at the edge and in the cloud, supporting a wide range of applications, including satellite communications and energy grid monitoring.

Real-time ML

Anomaly Detection

Bytewax can process real-time IoT data with machine learning models to enhance anomaly detection, efficiently predicting equipment failures and spotting unusual activity, which effectively reduces downtime and extends asset lifespan.

Monitoring

Sensor Analysis

Bytewax enables real-time processing and analysis of data from environmental sensors. This facilitates early warning systems, predictive modeling, and real-time decision-making for environmental protection and disaster response.

Iot Connectors

Popular Connectors among Our IoT Community

Premium

MQTT

Sink & Source
Premium

RabbitMQ

Sink & Source
Open source

Apache Kafka

Source & Sink
Premium

Azure IoT Data Hub

Sink
Open source

Redpanda

Source & Sink
Premium

Azure EventHub

Sink & Source
Reference Architecture

Process Real-Time Datastreams on the Edge and Cloud

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Bytewax's edge processing capability opens up new possibilities for IoT stream processing architectures. It allows for aggregating streams and running initial ML workloads on edge devices, with more powerful ML and streaming processes handled in the cloud.

Community Voices

Hear from our IoT Builders about Streaming with Bytewax

As of today Bytewax outperforms the previous Kafka JS based service and has been running uninterrupted for 6 months, without a single incident despite continuously onboarding new customers.

We use Flink a lot internally, but after picking up Bytewax we are looking for more and more real-time ML workloads to use Bytewax with because we find it to be more accessible and faster to set up than Flink

We went from 5 days of training to 5 minutes DIY. Anyone with a limited Python background can just get going immediately. A defensible 10x reduction in infrastructure cost.

The native integration of Bytewax with the Redpanda Schema Registry, marks a significant milestone for Python developers building streaming data solutions.

Bytewax is simple enough that we can quickly prove ahead of time that we can solve a problem and then use the same tool to scale it and move it to production.