# Bulk Replication

DevFeed: [Bulk Replication](<https://devfeed.tech/articles/bulk-replication-34498.md>)

Original publisher: [Read original article](<https://tapoueh.org/blog/2013/03/bulk-replication/>)

Author: Dimitri Fontaine PostgreSQL Major Contributor; Author

Published: 2013-03-18T13:54:00Z

Content type: tutorial

Language: en

Sources: [Dimitri Fontaine](<https://devfeed.tech/sources/dimitri-fontaine.md>)

Topics: [Replication](<https://devfeed.tech/topics/replication.md>), [data](<https://devfeed.tech/topics/data.md>), [Python](<https://devfeed.tech/topics/python.md>)

Tags: [batch](<https://devfeed.tech/tags/batch.md>), [concurrently](<https://devfeed.tech/tags/concurrently.md>), [delete](<https://devfeed.tech/tags/delete.md>), [handler](<https://devfeed.tech/tags/handler.md>), [insert](<https://devfeed.tech/tags/insert.md>), [network](<https://devfeed.tech/tags/network.md>), [replication](<https://devfeed.tech/tags/replication.md>)

## AI overview

This article explains how batch update techniques can be applied to trigger-based data replication with SkyTools and londiste. It describes using londiste handlers to process batches of replication events, including bulk-loading methods for inserting, updating, and deleting data.

## Source excerpt

In the previous article here we talked about how to properly update more than one row at a time, under the title Batch Update. We did consider performances, including network round trips, and did look at the behavior of our results when used concurrently. A case where we want to apply the previous article approach is when replicating data with a trigger based solution, such as SkyTools and londiste. Well, maybe not in all cases, we need to have a amount of UPDATE trafic worthy of setting up the solution. As soon as we know we're getting to replay important enough batches of events, though, certainly using the batch update tricks makes sense.