With multiple ways to CDC (triggers, joins, true transaction binary tracking...etc) and even more architectural questions to ask (streaming vs batch, throughput vs latency, structured vs complex data...etc) developing a streaming data ingestion strategy leveraging modern, multi-modal CDC can be a task. There are so many options, and many pitfalls to avoid. Deploying real-time data ingestion with precision and ensuring data capture exactly once, is critical to helping your BI teams produce accurate insights. In short...you have to get it right.

WATCH THE VIDEO RECAP

In this session, we explored:

• How to arrive at optimal, streaming data ingestion using modern CDC (Change Data Capture)
• The challenges of Data Silos created by Legacy Data Ingestion Strategies for CDC and ETL
• Simplifying streaming ingestion, and affording flexibility for lingering batch processes
• Various methods of Change Data Capture and which to choose to drive performance

We also:

• Demonstrated how to simplify streaming data ingestion with Equalum’s best of breed Change Data Capture and Data Ingestion Platform and no-code UI

MEET YOUR MODERATOR

Alton Dinsmore, Senior Data Architect, Equalum
Alton is a data veteran (Oracle, Dell EMC, MariaDB and more) with over 40 years of design and architect experience around enterprise data solutions and applications. He has helped many companies implement successful projects around large data, high performance, large number of users, large number of transactions, clustering, as well as high availability and disaster recovery. Alton has led engineering teams, projects, and data operations, helping companies redesign or improve upon implementation to achieve their desired objectives.

Deploying a Near-Real Time Data Ingestion Strategy with Modern Change Data Capture (CDC) - Equalum Office Hours

September 2020