A breakdown of the concepts to get started on this mighty analytical search engine.

Elasticsearch is a distributed, scalable analytical search engine that supports complex aggregations for unstructured data.

Akin to NoSQL data stores, Elasticsearch is built to handle unstructured data formats and dynamically determine fields’ data types. Its primary data format is JSON _(Javascript Object Notation) _documents. JSON’s schema-less format allows for flexible data storage and ease of adding data without managing or creating relations.

However, Elasticsearch isn’t necessarily interchangeable to NoSQL databases. Elasticsearch differs from NoSQL databases and has its own set of limitations. For example, Elasticsearch distributed system adds a layer of complexity when performing transactions. Although it isn’t impossible to do distributed transactions, it’s ideal to avoid them if possible to simplify the process.

Elasticsearch also assumes enough memory is provided to its instances. Therefore it’s not too keen on handling OutOfMemory errors. As a result, it makes Elasticsearch less robust than other data storage systems.

Elasticsearch is commonly used as a secondary tool alongside other types of databases. And it’s crucial to remember Elasticsearch is built for speed. It’s ideal for searching and filtering documents.

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