Reducing environmental impact through real-time data streaming

When we think of data, the primary focus is often on its potential to reduce costs, increase revenue, improve customer experiences and enhance operational efficiencies. Importantly, placing focus on good practices for secure data management is essential. However, there is one often overlooked aspect of data management: its environmental impact. Various estimates indicate that every gigabyte of data stored in the cloud uses between 3 and 7 kWh of energy per gigabyte. This means that large-scale data storage, often measured in terabytes, can contribute significantly to an organisation’s overall carbon footprint.

The good news is that data-driven technologies can support a more sustainable future. ‘Green coding’, a practice that focuses on efficiency and sustainability in software development, is gaining momentum, alongside efforts to increase transparency in tech supply chains and promote ethical data storage practices. Optimising how organisations process data can also significantly decrease their carbon footprint.

Modernising data management strategies with sustainability in mind not only benefits the planet but also lends to stronger business outcomes. According to 2024 SAP research, 68% of Australian businesses see a moderate to strong relationship between sustainability and their organisation’s competitiveness, as well as profitability.

Below are three ways modernising data infrastructure through data streaming can benefit the environment.

Energy efficiency in continuous processing

When it comes to managing data, businesses often choose between batch processing, where large volumes of data are processed at scheduled intervals, and data streaming, where data is continuously processed in real time as it arrives.

There’s a common misconception that continuous streaming is less efficient because it requires constant processing power. Some compare it to leaving a TV on standby, which is worse than turning it ‘on and off’ when needed. In reality, the opposite is true.

Batch processing causes sudden spikes in power consumption, making it far less efficient than a continuous low-level stream. Using the TV analogy again, batch processing is like turning a TV on and off 500 times a minute instead of leaving it in standby mode. The constant surges actually lead to the consumption of considerably more energy. But by switching to real-time data streaming, businesses can lower their energy consumption and create a more efficient system.

Creating predictable data workloads

Alongside significantly reducing CPU usage, adopting real-time data streaming leads to more predictable processing. By switching from sudden spikes in processing to a continuous flow, organisations can more accurately forecast their computing and infrastructure requirements.

A great example of this in action is Apache Flink, an open-source stream-processing framework widely used for real-time data streaming. With Flink Actions, the operations applied to data streams in Apache Flink, teams gain access to real-time analytics, which helps them develop a clear and reliable understanding of their usage. This means less reliance on costly cloud contingency plans to manage unexpected surges.

The result? Sharper efficiency, lower costs and more sustainable, predictable processing systems.

Serverless sustainability

Lastly, taking a serverless approach to data takes the sustainability benefits of data streaming to a new level. This is because it automatically scales computing resources in real time as workloads fluctuate, ensuring more responsive and cost-effective data processing with no manual intervention. By only spinning up infrastructure when active processing occurs, this method aligns with green coding principles — optimising resources and limiting energy waste.

In turn, developers can focus on writing efficient, event-driven functions that consume fewer resources, rather than grappling with the bottlenecks associated with batch processing. This shift in focus can ultimately help to promote sustainability throughout the entire software development life cycle.

Choosing green providers

Despite all of these benefits, there is an important consideration: while green coding and data streaming can go a long way toward reducing an organisation’s carbon footprint, sustainability also depends on the cloud suppliers behind the data storage.

Having said that, many cloud providers are increasingly prioritising going green. Not only is sustainability the right thing to do, but it is also marketable, efficient and cost-effective. Leading serverless providers often use renewable energy sources to power their data centres, further reducing the carbon footprint of serverless computing frameworks. This shift towards green energy is integral to sustainable computing practices.

For Australian businesses handling high-volume, event-driven data, combining real-time data streaming with a sustainable cloud provider offers a significant leap to a more climate-conscious, data-driven future.

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