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SparkPipe: Stream OT Data to the Cloud with MQTT Sparkplug. No Code. No ETL. No Hassle

SparkPipe connects your edge gateways to your preferred cloud services in minutes, streaming real-time OT data via MQTT Sparkplug, without middleware or manual integration.

Launch SparkPipe on AWS

Free 31-day trial

Sparkplug Compatible logo with a blue icon of a spark and the text ‘Sparkplug Compatible’ next to it.

What is SparkPipe

A Streamlined, Cloud-Ready Pipeline for OT Data Built on MQTT Sparkplug

SparkPipe is a lightweight, no-code data pipeline that ingests OT data from any MQTT Sparkplug-compliant edge gateway or device and streams it directly to your cloud services. It eliminates the need for ETL pipelines, custom integration logic, and middleware layers, offering a streamlined, secure way to deliver operational data from the edge to the cloud. From real-time analytics to centralized monitoring and storage, SparkPipe gives you a clean, standards-based bridge between your edge infrastructure and cloud-native applications.

SparkPipe architecture for MQTT Sparkplug cloud OT data pipeline
SparkPipe architecture for MQTT Sparkplug cloud OT data pipeline

How It Works

From Edge to Cloud in Three Simple Steps

Diagram showing OT data flow from edge wind turbines through SparkPipe and AWS to cloud platforms like Snowflake, Kafka, and MongoDB

Data is Published
from Edge Devices

SparkPipe Ingests and Processes the Data

Data is Delivered to the Cloud
via Built-In Connectors

Any MQTT Sparkplug-compliant gateway or device publishes real-time OT data to your existing MQTT broker.

SparkPipe connects to the MQTT broker, automatically interprets payloads, and prepares the data for cloud delivery, with no scripting or data mapping required.

Choose your destination: Kafka, AWS IoT SiteWise, Snowflake, MongoDB, or others. SparkPipe streams your data directly to these services with minimal configuration.

No vendor lock-in. No custom logic

Configuration via single TOML file

Built-in connectors, no middleware needed

Use SparkPipe to stream contextualized OT data to the cloud

Compatible with any MQTT Sparkplug-compliant device.
No code and no transformation layers required
Built-in connectors for Kafka, AWS IoT SiteWise, Snowflake, MongoDB

Compatible with any MQTT Sparkplug-compliant device.

No code, no transformation layers.

Includes built-in connectors for Kafka, AWS IoT SiteWise, Snowflake, MongoDB, and more.

Lightweight runtime, deployed in your own AWS account
Designed for speed, simplicity, and interoperability

Lightweight runtime, deployed in your own AWS account.

Designed for speed, simplicity, and interoperability.

What SparkPipe Enables

SparkPipe delivers contextualized, structured OT data to your cloud platforms,  unlocking industrial use cases
through the services you already trust.

AWS IoT SiteWise logo

AWS IoT SiteWise

SparkPipe provides a no-code integration that automatically creates asset models and assets in SiteWise based on your edge data structure. It continuously ingests real-time OT data into the SiteWise time-series engine, enabling immediate use in KPI computation, dashboards, and AWS-native analytics, without manual setup or custom code.

Snowflake

In Snowflake, SparkPipe enables cloud-based analytics by delivering contextualized OT data into a scalable data platform. This data can be seamlessly combined with information from industrial and enterprise systems, such as ERP, MES, CMMS, or any other relevant data source, enabling unified queries, dashboards, anomaly detection, and predictive analytics using standard SQL tools.

Snowflake logo
Kafka logo

Apache Kafka

Kafka becomes the foundation for real-time industrial data pipelines when powered by SparkPipe. Events and telemetry from the edge are streamed directly into Kafka topics, enabling automation, stream processing with Flink or Kafka Streams, and scalable, decoupled architectures between OT systems and enterprise applications.

MongoDB Time Series

With MongoDB Time Series, SparkPipe enables efficient long-term storage of high-frequency industrial data. Time-stamped sensor readings and events are stored in a queryable format, optimized for historical analysis, diagnostics, and visualization using MongoDB’s native tools or integrations.

MongoDB logo

Deployment & Security

Deploy with Confidence. Run on Your Terms.

AWS logo icon representing self-hosted deployment in your AWS account
Rocket launch icon representing simple deployment and minimal system footprint
Security shield icon representing default security features

Self-Hosted in Your AWS Account

Simple Launch, Minimal Footprint

Secure by Default

SparkPipe runs entirely within your cloud environment using a hardened AMI.

No agents. No licenses. Launch from the AWS Marketplace in minutes.

TLS encryption, IAM role support, VPC integration, hardened Linux base.

Sparkplug Compatible logo indicating certified MQTT Sparkplug compatibility

SparkPipe is Sparkplug Compatible Software

SparkPipe fully implements the Sparkplug specification and provides the highest level of compatibility. Being an official Sparkplug Compatible software, guarantees smooth integration with Sparkplug Host Applications. This translates to simplified data exchange and optimized workflows within your IIoT projects.


Get Started

Deploy SparkPipe and Start Streaming OT Data to the Cloud Today

Launch SparkPipe directly from the AWS Marketplace and start streaming contextualized, structured OT data from your edge devices to your preferred cloud platforms.

SparkPipe logo – cloud-ready no-code pipeline for OT data streaming with MQTT Sparkplug compatibility
Green checkmark inside a green hexagon

No code

Green checkmark inside a green hexagon

No lock-in

Green checkmark inside a green hexagon

Free 31-day trial

Whether you’re building analytics dashboards, digital twins, or event-driven pipelines, SparkPipe gets your OT data where it needs to go — reliably, securely, and instantly.

Launch SparkPipe on AWS

Runs in your own cloud environment — Prebuilt, production-ready AMI

SparkPipe: Stream OT Data to the Cloud with MQTT Sparkplug. No Code. No ETL. No Hassle

Launch SparkPipe on AWS

Free 31-day trial

SparkPipe connects your edge gateways to your preferred cloud services in minutes,
streaming real-time OT data via MQTT Sparkplug, without middleware or manual integration.

Sparkplug Compatible logo with a blue icon of a spark and the text ‘Sparkplug Compatible’ next to it.

What is SparkPipe

A Streamlined, Cloud-Ready Pipeline for OT Data Built on MQTT Sparkplug

SparkPipe is a lightweight, no-code data pipeline that ingests OT data from any MQTT Sparkplug-compliant edge gateway or device and streams it directly to your cloud services. It eliminates the need for ETL pipelines, custom integration logic, and middleware layers, offering a streamlined, secure way to deliver operational data from the edge to the cloud. From real-time analytics to centralized monitoring and storage, SparkPipe gives you a clean, standards-based bridge between your edge infrastructure and cloud-native applications.

SparkPipe architecture for MQTT Sparkplug cloud OT data pipeline

How It Works

From Edge to Cloud in Three Simple Steps

Data is Published
from Edge Devices

Data is Published from 
Edge Devices

Any MQTT Sparkplug-compliant gateway or device publishes real-time OT data to your existing MQTT broker.

No vendor lock-in. No custom logic

From Edge to Cloud in Three Simple Steps
SparkPipe Ingests and Processes the Data

SparkPipe Ingests and Processes the Data

SparkPipe connects to the MQTT broker, automatically interprets payloads, and prepares the data for cloud delivery, with no scripting or data mapping required.

Configuration via single TOML file

From Edge to Cloud in Three Simple Steps
Data is Delivered to the Cloud
via Built-In Connectors

Data is Delivered to the Cloud via Built-In Connectors

Choose your destination: Kafka, AWS IoT SiteWise, Snowflake, MongoDB, or others. SparkPipe streams your data directly to these services with minimal configuration.

Built-in connectors, no middleware needed

Use SparkPipe to stream contextualized OT data to the cloud

Compatible with any MQTT Sparkplug-compliant device.

Compatible with any MQTT Sparkplug-compliant device.

No code and no transformation layers required

No code, no transformation layers.

Built-in connectors for Kafka, AWS IoT SiteWise, Snowflake, MongoDB

Includes built-in connectors for Kafka, AWS IoT SiteWise, Snowflake, MongoDB, and more.

Lightweight runtime, deployed in your own AWS account

Lightweight runtime, deployed in your own AWS account.

Designed for speed, simplicity, and interoperability

Designed for speed, simplicity, and interoperability.

What SparkPipe Enables

SparkPipe delivers contextualized, structured OT data to your cloud platforms,  unlocking industrial use cases through the services you already trust.

AWS IoT SiteWise logo

AWS IoT SiteWise

SparkPipe delivers contextualized, structured OT data to your cloud platforms,  unlocking industrial use cases through the services you already trust.

Snowflake logo

Snowflake

In Snowflake, SparkPipe enables cloud-based analytics by delivering contextualized OT data into a scalable data platform. This data can be seamlessly combined with information from industrial and enterprise systems, such as ERP, MES, CMMS, or any other relevant data source, enabling unified queries, dashboards, anomaly detection, and predictive analytics using standard SQL tools.

Kafka logo

Apache Kafka

Kafka becomes the foundation for real-time industrial data pipelines when powered by SparkPipe. Events and telemetry from the edge are streamed directly into Kafka topics, enabling automation, stream processing with Flink or Kafka Streams, and scalable, decoupled architectures between OT systems and enterprise applications.

MongoDB logo

MongoDB Time Series

With MongoDB Time Series, SparkPipe enables efficient long-term storage of high-frequency industrial data. Time-stamped sensor readings and events are stored in a queryable format, optimized for historical analysis, diagnostics, and visualization using MongoDB’s native tools or integrations.


Deployment & Security

Deploy with Confidence. Run on Your Terms

AWS logo icon representing self-hosted deployment in your AWS account

Self-Hosted in Your AWS Account

SparkPipe runs entirely within your cloud environment using a hardened AMI.

Rocket launch icon representing simple deployment and minimal system footprint

Simple Launch, Minimal Footprint

No agents. No licenses. Launch from the AWS Marketplace in minutes.

Security shield icon representing default security features

Secure by Default

TLS encryption, IAM role support, VPC integration, hardened Linux base.

Get Started

Deploy SparkPipe and Start Streaming OT Data to the Cloud Today

Launch SparkPipe directly from the AWS Marketplace and start streaming contextualized, structured OT data from your edge devices to your preferred cloud platforms.

SparkPipe logo – cloud-ready no-code pipeline for OT data streaming with MQTT Sparkplug compatibility
Green checkmark inside a green hexagon

No code

Green checkmark inside a green hexagon

No lock-in

Green checkmark inside a green hexagon

Free 31-day trial

Whether you’re building analytics dashboards, digital twins, or event-driven pipelines, SparkPipe gets your OT data where it needs to go — reliably, securely, and instantly.

Launch SparkPipe on AWS

Runs in your own cloud environment — Prebuilt, production-ready AMI

SparkPipe: Stream OT Data to the Cloud with MQTT Sparkplug. No Code. No ETL. No Hassle

Launch SparkPipe on AWS

Free 31-day trial

SparkPipe connects your edge gateways to your preferred cloud services in minutes,
streaming real-time OT data via MQTT Sparkplug, without middleware or manual integration.

Sparkplug Compatible logo with a blue icon of a spark and the text ‘Sparkplug Compatible’ next to it.

What is SparkPipe

A Streamlined, Cloud-Ready Pipeline for OT Data Built on MQTT Sparkplug

SparkPipe is a lightweight, no-code data pipeline that ingests OT data from any MQTT Sparkplug-compliant edge gateway or device and streams it directly to your cloud services. It eliminates the need for ETL pipelines, custom integration logic, and middleware layers, offering a streamlined, secure way to deliver operational data from the edge to the cloud. From real-time analytics to centralized monitoring and storage, SparkPipe gives you a clean, standards-based bridge between your edge infrastructure and cloud-native applications.

SparkPipe architecture for MQTT Sparkplug cloud OT data pipeline

How It Works

From Edge to Cloud in Three Simple Steps

Data is Published
from Edge Devices

Data is Published from 
Edge Devices

Any MQTT Sparkplug-compliant gateway or device publishes real-time OT data to your existing MQTT broker.

No vendor lock-in No custom logic

From Edge to Cloud in Three Simple Steps
SparkPipe Ingests and Processes the Data

SparkPipe Ingests and Processes the Data

SparkPipe connects to the MQTT broker, automatically interprets payloads, and prepares the data for cloud delivery, with no scripting or data mapping required.

Configuration via single TOML file

From Edge to Cloud in Three Simple Steps
Data is Delivered to the Cloud
via Built-In Connectors

Data is Delivered to the Cloud via Built-In Connectors

Choose your destination: Kafka, AWS IoT SiteWise, Snowflake, MongoDB, or others. SparkPipe streams your data directly to these services with minimal configuration.

Built-in connectors, no middleware needed

Use SparkPipe to stream contextualized OT data to the cloud

Compatible with any MQTT Sparkplug-compliant device.

Compatible with any MQTT Sparkplug-compliant device.

No code and no transformation layers required

No code, no transformation layers.

Built-in connectors for Kafka, AWS IoT SiteWise, Snowflake, MongoDB

Includes built-in connectors for Kafka, AWS IoT SiteWise, Snowflake, MongoDB, and more.

Lightweight runtime, deployed in your own AWS account

Lightweight runtime, deployed in your own AWS account.

Designed for speed, simplicity, and interoperability

Designed for speed, simplicity, and interoperability.

What SparkPipe Enables

SparkPipe delivers contextualized, structured OT data to your cloud platforms,  unlocking industrial use cases through the services you already trust.

AWS IoT SiteWise logo

AWS IoT SiteWise

SparkPipe provides a no-code integration that automatically creates asset models and assets in SiteWise based on your edge data structure. It continuously ingests real-time OT data into the SiteWise time-series engine, enabling immediate use in KPI computation, dashboards, and AWS-native analytics, without manual setup or custom code.

Snowflake logo

Snowflake

In Snowflake, SparkPipe enables cloud-based analytics by delivering contextualized OT data into a scalable data platform. This data can be seamlessly combined with information from industrial and enterprise systems, such as ERP, MES, CMMS, or any other relevant data source, enabling unified queries, dashboards, anomaly detection, and predictive analytics using standard SQL tools.

Kafka logo

Apache Kafka

Kafka becomes the foundation for real-time industrial data pipelines when powered by SparkPipe. Events and telemetry from the edge are streamed directly into Kafka topics, enabling automation, stream processing with Flink or Kafka Streams, and scalable, decoupled architectures between OT systems and enterprise applications.

MongoDB logo

MongoDB Time Series

With MongoDB Time Series, SparkPipe enables efficient long-term storage of high-frequency industrial data. Time-stamped sensor readings and events are stored in a queryable format, optimized for historical analysis, diagnostics, and visualization using MongoDB’s native tools or integrations.


Deployment & Security

Deploy with Confidence. Run on Your Terms

AWS logo icon representing self-hosted deployment in your AWS account

Self-Hosted in Your AWS Account

SparkPipe runs entirely within your cloud environment using a hardened AMI.

Rocket launch icon representing simple deployment and minimal system footprint

Simple Launch, Minimal Footprint

No agents. No licenses. Launch from the AWS Marketplace in minutes.

Security shield icon representing default security features

Secure by Default

TLS encryption, IAM role support, VPC integration, hardened Linux base.

Get Started

Deploy SparkPipe and Start Streaming OT Data to the Cloud Today

Launch SparkPipe directly from the AWS Marketplace and start streaming contextualized, structured OT data from your edge devices to your preferred cloud platforms.

SparkPipe logo – cloud-ready no-code pipeline for OT data streaming with MQTT Sparkplug compatibility
Green checkmark inside a green hexagon

No code

Green checkmark inside a green hexagon

No lock-in

Green checkmark inside a green hexagon

Free 31-day trial

Whether you’re building analytics dashboards, digital twins, or event-driven pipelines, SparkPipe gets your OT data where it needs to go — reliably, securely, and instantly.

Launch SparkPipe on AWS

Runs in your own cloud environment — Prebuilt, production-ready AMI

FAQ’s

What is SparkPipe and how does it use MQTT Sparkplug?

SparkPipe is a no-code data pipeline that ingests OT data from MQTT Sparkplug-compliant devices and streams it directly to cloud services. By interpreting Sparkplug payloads automatically, SparkPipe eliminates the need for ETL pipelines or custom scripts and enables seamless edge-to-cloud integration with platforms like AWS IoT SiteWise, Kafka, Snowflake, and MongoDB Time Series.

What’s the difference between MQTT and MQTT Sparkplug?

MQTT is a lightweight messaging protocol widely used in IoT. MQTT Sparkplug builds on top of MQTT to define a standardized data model and messaging conventions for industrial systems. This ensures that OT data is contextualized, structured, and ready for cloud analytics. SparkPipe is specifically designed to support Sparkplug payloads end-to-end.

What is the Snowflake connector in SparkPipe used for?

The built-in Snowflake connector in SparkPipe streams contextualized OT data directly into Snowflake. Once there, this data can be combined with ERP, MES, or CMMS datasets, making it easy to run SQL queries, dashboards, anomaly detection, or predictive analytics at scale.

How can I stream OT data to Kafka without writing code?

SparkPipe includes a native Kafka connector that publishes MQTT Sparkplug data into Kafka topics in real time. This allows you to trigger workflows, send alerts, or feed stream processors like Flink — all without writing custom producers or middleware.

Can I use SparkPipe with my existing MQTT broker?

Yes. SparkPipe connects to your existing MQTT broker and automatically detects Sparkplug-compliant devices. You don’t need to replace your broker or disrupt your existing setup.

Is SparkPipe compatible with Ignition and Sparkplug-enabled devices?

Yes. SparkPipe works with any Sparkplug B-compliant device or gateway — including Ignition by Inductive Automation with Cirrus Link modules — making it highly interoperable with existing OT infrastructures.

Why choose SparkPipe instead of building custom scripts or DIY pipelines?

Custom scripts and homegrown pipelines often create technical debt, requiring constant maintenance, troubleshooting, and updates as systems evolve. SparkPipe prevents this by providing a no-code, stateless, and secure pipeline with built-in connectors for AWS IoT SiteWise, Snowflake, Apache Kafka, MongoDB Time Series, and more to come. It’s purpose-built for OT data, so you can deploy quickly, scale easily, and stay ready for future cloud platforms without the burden of maintaining custom integrations.

What does it mean that SparkPipe is stateless?

Stateless means SparkPipe doesn’t store or manage persistent data internally. It continuously forwards OT data from edge devices to cloud destinations. This design makes it lightweight, resilient, and easy to scale without state synchronization.

How does SparkPipe keep OT data secure in the cloud?

SparkPipe runs fully inside your AWS environment, using TLS encryption, IAM roles for access management, and VPC isolation. Since it is self-hosted, you maintain complete control over your infrastructure and data security.

Can SparkPipe be used for digital twins or predictive maintenance?

Yes. While SparkPipe doesn’t perform analytics itself, it delivers structured OT data into platforms such as AWS IoT SiteWise or Snowflake. These services can then be used to build digital twins, monitor KPIs, or run predictive maintenance models powered by machine learning.

FAQ’s

What is SparkPipe and how does it use MQTT Sparkplug?

SparkPipe is a no-code data pipeline that ingests OT data from MQTT Sparkplug-compliant devices and streams it directly to cloud services. By interpreting Sparkplug payloads automatically, SparkPipe eliminates the need for ETL pipelines or custom scripts and enables seamless edge-to-cloud integration with platforms like AWS IoT SiteWise, Kafka, Snowflake, and MongoDB Time Series.

What’s the difference between MQTT and MQTT Sparkplug?

MQTT is a lightweight messaging protocol widely used in IoT. MQTT Sparkplug builds on top of MQTT to define a standardized data model and messaging conventions for industrial systems. This ensures that OT data is contextualized, structured, and ready for cloud analytics. SparkPipe is specifically designed to support Sparkplug payloads end-to-end.

What is the Snowflake connector in SparkPipe used for?

The built-in Snowflake connector in SparkPipe streams contextualized OT data directly into Snowflake. Once there, this data can be combined with ERP, MES, or CMMS datasets, making it easy to run SQL queries, dashboards, anomaly detection, or predictive analytics at scale.

How can I stream OT data to Kafka without writing code?

SparkPipe includes a native Kafka connector that publishes MQTT Sparkplug data into Kafka topics in real time. This allows you to trigger workflows, send alerts, or feed stream processors like Flink — all without writing custom producers or middleware.

Can I use SparkPipe with my existing MQTT broker?

Yes. SparkPipe connects to your existing MQTT broker and automatically detects Sparkplug-compliant devices. You don’t need to replace your broker or disrupt your existing setup.

Is SparkPipe compatible with Ignition and Sparkplug-enabled devices?

Yes. SparkPipe works with any Sparkplug B-compliant device or gateway — including Ignition by Inductive Automation with Cirrus Link modules — making it highly interoperable with existing OT infrastructures.

Why choose SparkPipe instead of building custom scripts or DIY pipelines?

Custom scripts and homegrown pipelines often create technical debt, requiring constant maintenance, troubleshooting, and updates as systems evolve. SparkPipe prevents this by providing a no-code, stateless, and secure pipeline with built-in connectors for AWS IoT SiteWise, Snowflake, Apache Kafka, MongoDB Time Series, and more to come. It’s purpose-built for OT data, so you can deploy quickly, scale easily, and stay ready for future cloud platforms without the burden of maintaining custom integrations.

What does it mean that SparkPipe is stateless?

Stateless means SparkPipe doesn’t store or manage persistent data internally. It continuously forwards OT data from edge devices to cloud destinations. This design makes it lightweight, resilient, and easy to scale without state synchronization.

How does SparkPipe keep OT data secure in the cloud?

SparkPipe runs fully inside your AWS environment, using TLS encryption, IAM roles for access management, and VPC isolation. Since it is self-hosted, you maintain complete control over your infrastructure and data security.

Can SparkPipe be used for digital twins or predictive maintenance?

Yes. While SparkPipe doesn’t perform analytics itself, it delivers structured OT data into platforms such as AWS IoT SiteWise or Snowflake. These services can then be used to build digital twins, monitor KPIs, or run predictive maintenance models powered by machine learning.

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