The future is here and the future needs more than your basic relational databases—cloud native databases like Apache Cassandra to the rescue. Amanda Moran discusses Apache Cassandra data modeling, how to do it right, and how to be successful with cloud native distributed databases by avoiding common mistakes.
Amanda Moran explains Apache Cassandra data modeling, how to do it right, and how you can be successful with cloud native distributed databases by avoiding common mistakes. Then she answers, Why all this migration headache? Can’t I just keep my relation database? Why do I want a cloud native database? What is data modeling in Apache Cassandra? Amanda shares what needs to be considered when moving from a relational database to Apache Cassandra or when moving from another NoSQL database to Apache Cassandra. She helps you take the right steps to get your data model correct and explains what the difference is between SQL and CQL. She then identifies common mistakes and how to fix them to be successful.
Amanda Moran is a developer advocate for DataStax. Her passion is bridging the gap between customers and engineering. She’s based in the Bay Area and has worked for HP, Lockheed Martin, Teradata, and an Apache Trafodion startup Esgyn. Amanda’s an Apache Committer and member of the PMC for Apache Trafodion. She’s worked on customer POCs, executive demos, distributed database cloud deployments, Python coding, data science workshops, conferences, Linux/Hadoop administration, and scripting—a little bit of everything. She has a master’s degree in computer science from Santa Clara university in 2012 and a BS in biology from the University of Washington. In her spare time, she loves running, hanging out with her dog, and finding reasons to go to Disneyland.
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