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What is Change Data Capture?
A method of detecting and capturing only the data that has changed in a source system since the last update – so your warehouse stays current without re-processing everything every time.
What it is
Change data capture (CDC) is like getting notifications instead of re-reading an entire newspaper every day. Instead of pulling all 500,000 rows from your CRM every night to check what changed, CDC detects only the 200 records that were added, updated, or deleted – and sends just those changes to your warehouse. This can work by reading database transaction logs, comparing timestamps, or using triggers that fire when data changes. The result is the same: your warehouse reflects near-real-time changes from your source systems without the overhead of full data reloads.
Why it matters for your business
Full data reloads are slow, expensive, and wasteful. When your ERP has 5 million transaction records and only 500 changed today, pulling all 5 million is like photocopying an entire filing cabinet because someone added one folder. CDC matters most for businesses that need current data – not just last night's snapshot. A $80M manufacturing company we worked with was running a full extract of their 12-million-row production database every night, taking 4 hours and frequently failing. CDC reduced that to incremental updates every 15 minutes, using 95% less compute and keeping their production dashboards current throughout the day.
How we approach it
We select the CDC method based on the source system. For databases that support log-based CDC (Postgres, MySQL, SQL Server), we read the transaction log directly – the most efficient and least intrusive approach. For SaaS tools that only offer API access, we use timestamp-based CDC: "give me everything that changed since the last time I asked." We implement deduplication and ordering logic downstream so that if the same record changes twice between syncs, your warehouse always reflects the latest state.
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Key Takeaways
- •CDC captures only what changed – not everything – saving compute time and keeping your data closer to real-time.
- •Full data reloads are wasteful for large tables. CDC reduces processing time by 90%+ in typical scenarios.
- •Log-based CDC is the gold standard for databases – efficient, non-intrusive, and captures deletes as well as inserts.
- •Near-real-time data means dashboards show today's numbers, not last night's snapshot.