batchUpdate

Batch update is a technique for applying multiple update operations collectively rather than individually. It aims to improve throughput and reduce communication overhead between an application and its data store by submitting updates in groups, often within a single transactional boundary when supported.

In relational databases, batch updates can be performed by sending several UPDATE statements in one batch, typically within one transaction. Some databases or drivers also allow updating multiple rows with a single statement by using a CASE expression to specify per-row values. Programmatic interfaces frequently provide batch APIs, such as JDBC’s batch update flow with methods like addBatch and executeBatch, which execute many prepared statements together.

Beyond relational databases, batch updates exist in other data stores and search systems. Document stores and search engines offer bulk or bulkWrite operations to update many documents in one call, while some data processing frameworks provide bulk update stages to apply transformations across a set of records efficiently.

Benefits of batch updates include reduced network latency, improved throughput, and stronger transactional guarantees when updates are encapsulated in a single transaction. Potential drawbacks include higher memory usage for large batches, the risk of partial failures that require complex error handling and retry logic, and the need to balance batch size against resource limits and latency requirements.

Best practices involve selecting an appropriate batch size, using prepared statements to avoid repeated parsing, wrapping updates in a transaction when atomicity is desired, monitoring error reports and retries, and ensuring idempotence where possible to recover gracefully from partial failures.