Steve Fernandes, Sr. Manager, Solutions Engineering at Confluent explains why streaming isn’t just faster: it’s smarter, more resilient, and in the long term, more cost-effective than batch processing
In a world where change can be triggered by a single tweet, batch processing is starting to look like yesterday’s solution to today’s real-time problems. Business leaders know the pressure. A price change by a competitor, a breaking geopolitical event, or an unexpected shift in consumer sentiment can instantly alter market dynamics. In this reality, waiting for the next scheduled data update is no longer good enough.
Real-time data streaming is no longer a luxury reserved for cutting-edge tech firms or financial giants, it’s a business imperative. And yet, many organisations still cling to batch-based architectures, not because they’re better, but because they’re familiar. But is that really the case?
Let’s take a closer look at why streaming isn’t just faster, it’s smarter, more resilient, and in the long term, more cost-effective.
The world works in real time-so should your data
We live in an age of instant gratification. Customers expect same-day delivery, instant notifications and seamless digital experiences. When you request a rideshare, the app isn’t waiting for an hourly batch update to match you with a driver, it’s using real-time streaming data to make that decision instantly. When your bank detects suspicious card activity, the fraud alert doesn’t arrive a day later, it’s immediate, based on real-time analytics.
This expectation for immediacy now stretches across every industry. In retail, streaming enables dynamic pricing and inventory optimisation. In manufacturing, it supports predictive maintenance, reducing downtime and saving costs. And in logistics, companies rely on live tracking data to reroute deliveries in response to traffic conditions or weather disruptions. The list goes on.
But beyond convenience, real-time data is increasingly linked to business resilience. In volatile environments, from markets to supply chains, organisations must be able to pivot instantly. A single tweet from a CEO can send a company’s stock soaring, or plummeting. A viral social media post can overwhelm an unprepared retailer. The companies that thrive are those with the agility to detect, interpret and respond to change as it happens. Real-time streaming makes that possible.
Yes, batch still has value-but it can’t do it all
Let’s be clear, batch processing still plays a role. It’s well-suited for high-volume, low-urgency tasks like end-of-day reporting or regulatory compliance. Many industries have used it successfully for decades, and it can be efficient for certain workloads.
But here’s the problem, batch can’t handle real-time use cases. Real-time, on the other hand, can handle batch ones. That’s why clinging to batch processing as your foundation is like building a Formula 1 car that only drives well in first gear. It limits your adaptability.
And here’s the kicker: as business needs evolve, many organisations find themselves duplicating infrastructure just to accommodate real-time use cases. They end up stitching together complex hybrid systems that are more expensive to maintain and harder to scale. Why not build for flexibility from the outset?
Streaming is more budget-friendly than you think
The most common objection to streaming is cost. It’s a fair concern, budgets are tight, and IT leaders are often asked to do more with less. But the perception that streaming is inherently more expensive doesn’t hold up under scrutiny.
Batch workloads typically require over-provisioning of resources to handle unpredictable spikes. Systems sit idle for much of the day, only to fire up in intense bursts. That stop-start nature is not only inefficient, it’s costly.
Streaming, in contrast, runs continuously but scales dynamically based on need. Data flows steadily, reducing resource waste and improving predictability in both performance and cost. The total cost of ownership (TCO) can be significantly lower, especially when you consider the long-term cost of maintaining dual infrastructures or dealing with the downstream effects of delayed decision-making.
The AI bottleneck that nobody’s talking about
Perhaps the most critical argument in favor of streaming is its impact on AI. As organizations invest heavily in AI and ML, they often overlook a key constraint: AI models are only as good as the data they receive, and when they receive it.
Batch-based architectures feed AI in large chunks. This slows training cycles and forces insights to emerge after the moment of action has passed. It creates blind spots which is a concern as if your fraud model or recommendation engine can’t see what’s happening right now, it can’t respond to it. In production, ML models encounter real-world data that can shift over time due to environmental changes. This difference from the training data, known as data drift, can lead to a decline in the model’s accuracy.
Streaming data feeds AI models in real time, enabling them to learn continuously, adapt to new patterns instantly, and deliver insights when they’re most valuable. That means smarter personalization, faster fraud detection, and more responsive customer service. In short, it’s not just about data pipelines, it’s about competitive advantage.
Rethinking architecture for a real-time world
At this point, the conversation should no longer be “batch or streaming?” It’s about designing systems that reflect the pace and complexity of the world we actually live in.
A single, unified streaming platform can handle both real-time and batch-style workloads. It simplifies infrastructure, reduces operational costs, and unlocks the flexibility needed to meet changing business demands. Companies that adopt this mindset aren’t just keeping up, they’re pulling ahead.
In financial services, for example, a bank might still need to snapshot global risk exposure each morning. But if a new policy announcement or natural disaster occurs five minutes later, they need to react instantly. A streaming-first architecture allows them to do both, from the same underlying data stream.
Build for the world we’re in
The world is not slowing down. Neither should your data.
Clinging to batch processing is like planning your week with yesterday’s newspaper. In today’s environment, where risk and opportunity shift by the minute, streaming gives you the visibility and agility to lead with confidence.
Yes, it’s a mindset shift. Yes, it may require investment. But the return is clear: a more resilient, efficient, and intelligent business that’s ready for whatever comes next.
