🧱 What Is Batch Processing?
Batch processing is when you process large chunks of data at once — usually on a schedule.
🧠 Think of:
- Doing laundry once a week: You collect dirty clothes for days, then wash them all at once.
- Processing all transactions at the end of the day.
✅ Characteristics:
- Works on stored (historical) data
- Runs in fixed intervals (e.g., hourly, daily)
- Often used for reports, analytics, backups
🌊 What Is Stream Processing?
Stream processing handles data immediately as it arrives — one event at a time.
🧠 Think of:
- Washing dishes as they get dirty, one by one
- Processing payments or chat messages in real time
✅ Characteristics:
- Works on real-time or near real-time data
- Processes each event as it comes in
- Used for alerts, dashboards, fraud detection, etc.
📊 Side-by-Side Comparison
| Feature | Batch Processing | Stream Processing |
|---|---|---|
| Timing | Scheduled (e.g., nightly) | Real-time or near real-time |
| Data Source | Stored files, tables | Continuous data streams (events) |
| Latency | High (minutes to hours) | Low (milliseconds to seconds) |
| Use Cases | Reports, ETL jobs, backups | Fraud detection, monitoring, notifications |
| Tools | Hadoop, Apache Spark (batch mode) | Apache Kafka, Apache Flink, Spark Streaming |
| Resource Usage | Higher spikes at intervals | More constant and distributed |
| Error Handling | Easier to retry whole batch | Must handle per-event gracefully |
🧠 Real-Life Examples
| Scenario | Batch or Stream? |
|---|---|
| Generating weekly sales reports | ✅ Batch |
| Sending a real-time notification | ✅ Stream |
| Syncing database backups nightly | ✅ Batch |
| Detecting credit card fraud | ✅ Stream |
| Analyzing logs from thousands of servers | ✅ Stream |
| Processing monthly payroll | ✅ Batch |
🚀 Tools You Might Hear About
| Tool | Type | Description |
|---|---|---|
| Apache Spark | Batch & Streaming | Powerful engine for both modes |
| Hadoop | Batch | Big data processing (map-reduce) |
| Apache Kafka | Stream | Message broker for streaming pipelines |
| Apache Flink | Stream | Low-latency event-driven processing |
| AWS Lambda + Kinesis | Stream | Serverless streaming in the cloud |
✅ Summary
- Batch processing = Process big data later
- Stream processing = Handle small data now
Both are useful — and often used together in modern systems:
- Stream for fast detection
- Batch for deep analysis