Consolidate high frequency sensor data in the cloud

Industrial companies use Quix to integrate large volumes of data from legacy systems, enabling use cases like real-time monitoring and analytics, predictive maintenance, digital twins, and more.

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Build data integration pipelines in minutes

Ingestion

Ingest data from all your real time sources in pure Python. Use out of the box connectors or customise connector templates for more flexibility.

Check out the full list of connectors

Transformation

Prepare your data with Quix Streams, our open source Python library for processing data in real time with streaming DataFrames. Use in-built operators for aggregation, windowing, filtering, group-by, branching, merging and more.

Enrich your data by connecting a cache.

Sink

Sink data to any database, lake or warehouse. Or send data back to your product.

Check out the full list of connectors

Ingestion

Ingest data from all your real time sources in pure Python. Use out of the box connectors or customise connector templates for more flexibility.

Check out the full list of connectors

Transformation

Sink

Sink data to any database, lake or warehouse. Or send data back to your product.

Check out the full list of connectors

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Get started with templates for common use cases

Check out our ready-to-run templates to get started with building your first integration.

Project template

Use case

Code snippet

Cut Kinesis costs by using Quix to pre-process data and write it to BigQuery

BiqQuery Data Engineers use Quix data pipelines to ingest large volumes of data from their operational estate on AWS. It's easier, cheaper and more flexible.

Data integration

Use case

Code snippet

Process regulated data with full compliance

Process patient data, clinical metrics, and operational insights while maintaining strict audit trails, data lineage. and PII protection measures.

PII protection

Project template

Use case

Code snippet

Integrate data from multiple sources into an Iceberg Lakehouse

Ingest data from multiple sources into Iceberg tables on S3. Use Quix Streams to normalize and standardize the data before it reaches your data lakehouse.

Data integration

ETL

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Choose the deployment option that fits your business

Run the Quix platform in the cloud or on the Edge, depending on your use case. Or build your own with Quix Streams, Apache Kafka and Kubernetes.

Quix Cloud

Enable your data teams to develop, deploy and govern connectors and pipelines.

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Quix Edge

Run Quix on-premise for non-negotiable compliance where serious scale meets extra low latency.

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Quix Streams

An open-source Python framework for real-time data processing and integrations with Streaming DataFrames.

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Explore the platform

Quix Streams repo

Quix customers do more with their data

Learn how customers are leveraging Quix to deliver more business value from their data.

Customer story

Optimizing manufacturing efficiency with streaming data and ML

How CloudNC makes better predictions for maintenance, generates insights with very low latency, and transforms its factory operations with streaming data.

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Interested in Quix Cloud?

Learn how companies are building data integration pipelines with Quix.

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Get started with Quix Streams

An open source library for processing data in Kafka using pure Python.

Quix Streams repo

Getting started with Quix

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Talk with our team of experts to learn more about how companies are building data integration pipelines with Quix.

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Ask our community

Join our Slack to get help with Quix Streams from our friendly developer community.

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