The main selling point of Elasticsearch is its simplicity to scale. Even by running it in a default setting, it immediately begins to showcase its scalability ability with an index of 5 shards and 1 replica (default index settings). The name Elastic in Elasticsearch refers to its clustering flexibility. You can easily scale up Elasticsearch by adding more machines into the mix in order to instantly increase capacity. It also includes the facility to handle automatic failover, so that planning for scalable and high availability architecture is greatly simplified.
To better comprehend Elasticsearch's scaling strategy, you will need to understand three main concepts: sharding, replica, and clustering. These are the core concepts that help drive elasticity in Elasticsearch.
A shard is a single Lucene index instance; it represents a slice of a bigger dataset. Sharding is a data partitioning strategy to make a large dataset more manageable. When dealing with an ever-growing...
