The popularity of stream data platforms has been increasing significantly in recent times, due to the requirement of real-time access to information. Enterprises are transitioning parts of their data infrastructure from traditional batch processing to streaming paradigm due to changing business needs and the need to get of Real-Time Insights on data as business events occur.
It's critical to understand the fundamental differences between stream and batch processing:
Stream Processing | Batch Processing | |
Data Volume | Smaller data chunks with a single or a small number of records. | Large volume, since data will be accumulated over a period of time and loaded incrementally in batches. |
Query Processing | Queries are processed on a smaller subset of data. Usually based on the timestamp of the data arrival. | Queries are processed on an entire dataset. |
Query Latency | Queries results are made available with extremely low latency—seconds or milliseconds. | Query results... |