Data has a shelf life. Some data is valuable only if processed in milliseconds; other data is best understood in massive aggregate blocks.
1The Batch World
Batch processing is about Volume. It processes large datasets that have been collected over a period of time. It's cost-effective because you can run it during off-peak hours and it doesn't require the system to be 'Always-On'. It's perfect for historical analysis, training massive ML models, and monthly financial reconciliation.
Mode: BATCH_PROCESSING
Trigger: SCHEDULED [00:00:00]
Volume: 10_TERABYTES
Latency: HIGH
Status: WAITING_FOR_MIDNIGHT2The Streaming World
Streaming is about Velocity. It processes data as it is generated (Event Streams). For AI, this is critical in Online Inference scenarios, such as detecting a cyber-attack as it happens or updating a navigation route based on traffic sensors. The challenge is 'State Management'—tracking what happened a second ago while the new data is flying in.
Mode: STREAMING
Trigger: EVENT_DRIVEN
Volume: CONTINUOUS
Latency: < 50ms
Status: LIVE_FLOWING