Basically, when you import data, it is indexed into an index. However, an index also refers to where are all the indexed data is stored. When data is added, the text is broken down into tokens (e.g. Index: This term has two meanings in Elasticsearch context. Below, is a list of common terms in Elasticsearch and their meaning. Elasticsearch terminologyĮlasticsearch uses its own terminology, which in some cases is different from typical database systems. To follow the examples in this article, you’ll also need to have Node.js installed (any version after v0.11.0 will do), as well as npm. To do so, you need the latest version of the Java Runtime Environment installed (see the Installing Elasticsearch section). You can run Elasticsearch on all major operating systems (Linux, Mac OS, and Windows). For following the examples in this article, a system with 2GB memory and a single CPU core will suffice. Although the recommended production setting is 64GB memory and as many CPU cores as possible, you can still run it on a resource-constrained system and get decent performance (assuming your data set is not huge). In this tutorial we will use the official client library.Įlasticsearch is very flexible when it comes to hardware and software requirements. It has many client libraries for almost any programming language, including for Node.js. This means that almost any operations can be done via a simple RESTful API using JSON data over HTTP. Elasticsearch is schema-free, stores data in JSON documents, and can automatically detect the data structure and type.Įlasticsearch is also completely API driven. When data is imported, it immediately becomes available for searching. Its horizontal scaling also means that it has a high availability by rebalancing the data if ever any nodes fail. It supports thousands of nodes for processing petabytes of data. Although Elasticsearch can perform the storage and retrieval of data, its main purpose is not to serve as a database, rather it is a search engine (server) with the main goal of indexing, searching, and providing real-time statistics on the data.Įlasticsearch has a distributed architecture that allows horizontal scaling by adding more nodes and taking advantage of the extra hardware. Elasticsearch is built on top of Apache Lucene, which is a high performance text search engine library.
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