Processing

Batch vs Streaming Processing Explained Simply If you’ve read Data Warehouse vs Data Lake vs Lakehouse, you know where data can live once it’s ready for analysis. But before it gets there, it has to be processed, and that raises another fundamental question, just as important as OLTP vs OLAP: when does that processing happen? That’s where batch processing and streaming processing come in. Think of it like doing laundry Imagine you’re in charge of laundry for a household. Batch processing is doing laundry once a week. You wait until there’s a full load, throw it all in the machine together, and process it in one go. Efficient, predictable, and you know exactly when it’ll be done, but if someone needs a clean shirt right now, they’re out of luck until the next load. Streaming processing is washing each item the moment it gets dirty. Nothing waits around: a shirt gets dirty, it gets washed immediately, one item at a time. Nobody waits for laundry day, but running the washing machine constantly, for one item at a time, is a lot less efficient than doing a full load. Same idea with data: do you wait and process it in chunks, or handle each piece the instant it arrives? ...

Batch vs Streaming Processing Explained Simply If you’ve read Data Warehouse vs Data Lake vs Lakehouse, you know where data can live once it’s ready for analysis. But before it gets there, it has to be processed — and that raises another fundamental question, just as important as OLTP vs OLAP: when does that processing happen? That’s where batch processing and streaming processing come in. Think of it like doing laundry Imagine you’re in charge of laundry for a household. Batch processing is doing laundry once a week. You wait until there’s a full load, throw it all in the machine together, and process it in one go. Efficient, predictable, and you know exactly when it’ll be done — but if someone needs a clean shirt right now, they’re out of luck until the next load. Streaming processing is washing each item the moment it gets dirty. Nothing waits around — a shirt gets dirty, it gets washed immediately, one item at a time. Nobody waits for laundry day, but running the washing machine constantly, for one item at a time, is a lot less efficient than doing a full load. Same idea with data: do you wait and process it in chunks, or handle each piece the instant it arrives? ...