In case you missed it, this blog post is a recap of Cassandra Lunch #19, covering the combined use of relational databases and Cassandra. We will discuss the advantages of using relational databases and Cassandra separately, before covering the advantages and methods for using both concurrently. 

In this blog, we recap Cassandra Lunch #18, where we had guest speaker, Ryan Quey, discuss and demo a personal project where he uses multiple technologies, including Cassandra and Kafka, to build an app that grabs podcast data related to topics he inputs, stores it, processes it and displays it on searchable a front-end. In case you missed it, the video of Cassandra Lunch is also embedded in the blog!

In Cassandra Lunch #16, we discuss Cassandra Anti-entropy which is a process of comparing the data of all replicas and updating each replica to the newest version. We also looked at repair and synchronization in Cassandra and how you can prepare for the unexpected.

In Cassandra Lunch #15, we discuss Cassandra Backup / Restoration. We discuss disaster avoidance, disaster recovery, and different tools that can be used for backup and restoration of your Cassandra data. Also, we discuss an example scenario of how someone has set up multi-node clusters and how they go about data backup and restoration. 

In case you missed Cassandra Lunch #14, we discussed methods for finding and diagnosing issues in Cassandra clusters. Starting off with why specialized diagnostic tools are necessary, we also discussed some outside resources that are useful in the monitoring of Cassandra clusters. We then moved on to some of Anant Corporation’s own resources for analyzing the performance of a Cassandra cluster, before diving into an example setup, demonstrating how Elastic and Kibana can make finding and diagnosing issues much easier.