Real-time data: Do you really need it or is batch enough?
Why chasing real-time solutions might be overkill for most businesses - and how batch processing often gets the job done.
Do you really need real-time data?
In my years working in data field, I’ve noticed something: a lot of companies feel like they must have real-time data pipelines. Whether it’s dashboards updating every second or live feeds of metrics, it seems like “real-time” has become the ultimate buzzword. But here’s the thing: most businesses don’t actually need real-time data.
Now, before you start thinking I’m against innovation, hear me out. Real-time systems absolutely have their place (I’ll get to that later), but in the majority of cases, a simple batch refresh every hour (or even once a day) gets the job done. And guess what? It’s cheaper, faster to build, easier to debug, and overall a lot less stressful to maintain.
Let me explain.
Why batch is usually enough:
1. 90% of use cases don’t require real-time
When it comes to standard business analytics, real-time data is almost never critical. Sales reports, campaign performance, or financial metrics? These things don’t change in meaningful ways second by second. Even updating your dashboards once an hour is usually more than enough for most decision-making processes.
With batch processing, you get:
Simplicity: No need to handle the complexity of streaming pipelines.
Faster Development: It’s quicker to implement and troubleshoot.
Easier Debugging: Batch jobs fail predictably and are easier to diagnose compared to real-time systems, where issues can pile up in milliseconds.
Think about it: Do your stakeholders need every-second updates on website traffic? Or can they wait an hour? In most cases, it’s the latter.
2. The cost of real-time is high
Building real-time systems isn’t just about writing a fancier pipeline - it’s also about handling infrastructure that supports high-throughput, low-latency data. It requires more engineering effort, more monitoring, and often more expensive tools.
Unless your company has a specific need for live data, this investment is rarely worth it. Instead, those resources could be spent on projects that drive real business value, like better data models or user-friendly reporting systems.
3. Real-time is often a buzzword
Many teams get swept up in the hype without asking the most important question: Why do we need this?
Here’s a pro tip: If you can’t clearly articulate the benefit of having real-time data for your business process, you probably don’t need it.
Does having a live sales dashboard fundamentally change your strategy? Likely not.
Is real-time campaign performance monitoring driving daily decisions? For most teams, no.
The truth is, the idea of real-time sounds exciting, but the reality is often over-engineered solutions for problems that don’t exist.
When real-time actually makes sense
That said, there are some cases where real-time data is a game-changer. If your business falls into one of these categories, then go for it:
1. Fraud detection
Real-time data is critical for detecting and responding to fraud as it happens. Payment processing systems, for example, rely on immediate action.
2. Logistics and transportation
If you’re managing fleets or tracking shipments, live data can help optimize routes and avoid delays.
3. IoT and predictive maintenance
Systems monitoring machines or devices often need to act on sensor data in real time to prevent failures or breakdowns.
4. Event-driven architecture (EDA)
For organizations using event-driven architecture, real-time data is essential. In this approach, systems need to communicate and respond to events as they happen, enabling more dynamic and responsive operations. This is especially important for applications where quick, automated reactions to events are critical.
But here’s the catch: these are edge cases, not the norm. For 90% of businesses, the need for real-time data just isn’t there.
The case for simplicity
At the end of the day, simplicity wins. Batch pipelines are easier to set up, debug, and scale. They don’t require complex infrastructure or constant monitoring. More importantly, they force you to think critically about your data needs:
What’s the goal?
Who’s using the data?
How often do they need updates?
Answering these questions can save your team countless hours chasing solutions you don’t need.
My two cents
This isn’t to say real-time data is bad - it’s just not always necessary. From my experience, almost everyone wants real-time data. It’s a hot topic in data pipelines, and teams often push for live pipelines. But in most cases, it’s not actually needed.
Too often, companies overcomplicate things, building real-time systems when a simple hourly or daily refresh would do just fine.
So, before diving into real-time, ask yourself: Do we really need this? Chances are, the answer is no. And that’s perfectly okay - simpler is usually better. 😊