Database / Google Spanner Database Interview questions
What is the difference between Data Boost and standard reads?
| Standard reads | Data Boost |
| Executed using the instance's provisioned nodes/processing units. | Executed on separate, serverless compute Google provisions on demand. |
| Competes with production transactional traffic for capacity. | Isolated from production traffic, so it doesn't affect transactional latency. |
| Billed as part of normal instance compute cost. | Billed separately, based on data processed for the analytical job. |
Data Boost is aimed at large analytical or batch reads, like exporting data to BigQuery or running a heavy reporting query, that would otherwise compete with the instance's OLTP workload for the same nodes. By offloading that read path to independent compute, transactional latency for the primary application stays stable even while a large scan or export runs in parallel.
What compute does Data Boost use for a read?
What kind of workload is Data Boost designed for?
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