To take advantage of the powerful search capabilities offered by Elasticsearch, many businesses will deploy Elasticsearch alongside existing relational databases. It will likely be necessary to keep Elasticsearch synchronized with the stored data in the associated relational database in such a scenario. (Source: Official Elastic Documentation)

This course will see how we can visualize RDBMS data using elk stack, and we will use Kibana to create beautiful visualizations and dashboards. We are going to do everything from scratch.

After completing this course, you’ll get an idea that ELK is not only used for logging purposes but can be used for visualizing RDBMS data. Additionally, I will use AWS RDS, GCP Compute Engine, AWS S3 in the course. I’m sure you’ll have fun learning these sessions.

"ELK" is the acronym for three open source projects: Elasticsearch, Logstash, and Kibana. Elasticsearch is a search and analytics engine. Logstash is a server‑side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a "stash" like Elasticsearch. Kibana lets users visualize data with charts and graphs in Elasticsearch.

The Elastic Stack is the next evolution of the ELK Stack. Oracle database products offer customers cost-optimized and high-performance versions of Oracle Database, the world's leading converged, multi-model database management system, as well as in-memory, NoSQL and MySQL databases.