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Project template

Use case

Code snippet

Cut the Cost of Handling Industrial IoT Data in the Cloud

Use cases:

Data integration

IoT

Heavy industry

An architecture diagram showing a real time data preprocessing pipeline or DAG

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About this template

The technologies you choose to handle your data processing needs can have a big impact on performance, maintainability and cost.

In this template we show you how to save 10x on getting IoT data from AWS to BigQuery:

Ingest large volumes of data from your operational estate on AWS while saving dramatically on AWS costs.
Process, map and analyze data using Quix Streams instead of Kinesis Data Analytics.
Get data into BigQuery cheaply by using the Quix BigQuery connector instead of Kinesis Firehose.

Using this template

Easily read data from different AWS services and sink it to BigQuery
Prepare data for BigQuery (data transformation, schema validation, downsampling, etc)
Move data between systems in a highly performant, cost-effective manner

Main project components

Technologies used

Amazon Kinesis

BigQuery

Interested in this use case?

If you'd like us to focus on building this template next, register your interest and let us know. You can also head over to the Quix Community Slack if you've got any questions.

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