Everyone I spoke with brought up the ecosystem’s stability and maturity as a cause of today’s accelerating adoption of CDC. The first three theories revolve around “Technology Readiness”. Once it’s out, the OLTP constraints disappear, and unlike batch ELT, it’s still live data. With CDC, getting the change feed out of the database takes a predictable amount of CPU and storage overhead, similar to enabling a read-replica. As a consequence, databases are a centralized source of a lot of organizational horse-trading. One person’s index to speed up their reads slows down another person’s writes. What is the value that CDC provides? One way to look at it:ĬDC architecturally decouples use-cases from the production database.ĭatabases are contended resources for organizations. What value does CDC provide?īefore we get into what is causing so many to turn to CDC now, let’s take a step back. I’ve compiled their insights and added takeaways for others evaluating CDC below. The evolution of data engineering teams.Arjun Narayan, CEO, and Cofounder of Materialize.ĬDC adoption is indeed accelerating.Taron Foxworth, Developer Advocate at Meroxa.Adam Boscarino, Manager of Data Engineering at Devoted Health.
#CHANGE DATA CAPTURE SOFTWARE#
Gunnar Morling, Open Source Software Engineer at Red Hat and Lead of Debezium.To make sure this wasn’t just a case of frequency illusion, I talked to four experts who have been working with CDC and related technologies for years and got their perspectives. What’s going on? Why is CDC suddenly cropping up everywhere? Change Data Capture (CDC) concepts have been around for 20+ years, but recently we’ve seen a step-change increase in discussion, companies, and tools in the CDC space.
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