Glossary

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Glossary / Evaluation and implementation guide

Change Data Capture (CDC)

Change Data Capture (CDC) is an integration pattern that detects and streams individual record changes from a source system, often by reading the database transaction log, so downstream systems receive only inserts, updates, and deletes instead of full copies.

It reduces load and preserves deletion events that polling misses.

A practical example

Example: your CRM holds 500,000 accounts, but only 2,000 change daily.

A CDC pipeline streams those 2,000 events to your data warehouse, while a nightly full export would move all 500,000 records and still miss hard deletions.

What to evaluate before investing

  • Ask whether CDC reads the source's transaction log or relies on timestamp polling, since the latter can miss deletes.
  • Check which source systems are supported and whether schema changes in the source break the pipeline.
  • Confirm how out-of-order or duplicate events are handled and whether you can replay history after an outage.

Limitations and tradeoffs

CDC pipelines are more complex to operate than batch exports: they need monitoring, checkpoint management, and schema-drift handling. Some vendors offer CDC only for specific sources or reserve log-based access for higher tiers.

Plan your next step with MeshLine

Connect this decision to your automation, organic marketing and customer lifecycle management. In a MeshLine demo, discuss your existing tools, the scope you need and how to measure the result.