# Too much Lag in CDC Pipeline (Confluent JDBC Sink Connector)
**URL:** https://forum.confluent.io/t/too-much-lag-in-cdc-pipeline-confluent-jdbc-sink-connector/9037
**Category:** Kafka Connect
**Created:** [9 November 2023 04:35 UTC](https://forum.confluent.io/t/too-much-lag-in-cdc-pipeline-confluent-jdbc-sink-connector/9037 "2023-11-09T04:35:35Z")
**Posts on this page:** 2
**Page:** 1
### Author:  [@jasir](https://forum.confluent.io/u/jasir)
#### Post date: [9 November 2023 04:35 UTC](https://forum.confluent.io/t/too-much-lag-in-cdc-pipeline-confluent-jdbc-sink-connector/9037/1 "2023-11-09T04:35:35Z")
I am currently managing a CDC (Change Data Capture) Pipeline for data streaming, where the source database is PostgreSQL and using the **Debezium Source Connector** is streaming data from Source PostgreSQL database to Kafka Topic with publishing rate of **4.5 messages/second.** The data is streamed to two separate PostgreSQL databases as the target, facilitated by Confluent JDBC Sink Connectors (Version 10.6.4) that read data from Kafka.
I am facing an issue with a persistent lag of approximately 45 messages in one of the Confluent JDBC Sink Connectors. Strikingly, the other Confluent JDBC Sink Connector, which feeds data into a different PostgreSQL database, experiences a lag of only 15 to 25 messages.
Despite my attempts to reduce this lag i tried to modify the following properties:
```auto
consumer.override.max.poll.records=1000
max.poll.interval.ms=180000
consumer.override.fetch.min.bytes = 101200
consumer.override.fetch.max.wait.ms = 1000
consumer.override.auto.commit.interval.ms=5
consumer.override.offset.flush.interval.ms=100
batch.size=4000
```
The lag has not reduced significantly. I am seeking suggestions on how to address this issue effectively and reduce the lag in the affected Confluent JDBC Sink Connector.
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### Author:  [@system](https://forum.confluent.io/u/system)
#### Post date: [9 December 2023 04:36 UTC](https://forum.confluent.io/t/too-much-lag-in-cdc-pipeline-confluent-jdbc-sink-connector/9037/2 "2023-12-09T04:36:29Z")
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