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Elasticsearch Setup

A perfect solution for working with unstructured data

Elasticsearch is an open source tool for searching and analysing various types of data. It is suitable for text, numerical, geospatial, structured and unstructured (NoSQL) data.

Why is Elasticsearch so popular?

Fast searching

Thanks to the use of a special data structure (so-called inverted index), it enables full-text search in almost real time.


The REST API can be used for many tasks, such as checking cluster status and performing index lookup operations.

Dealing with large amounts of data

The distributed nature of Elasticsearch allows you to scale hundreds to thousands of servers and process petabytes of data.

High availability

Elasticsearch recognises and discards false nodes in the cluster. Subsequently, the data are divided among the remaining nodes so that these are as accessible as possible.

How does Elasticsearch work?

What is Elasticsearch used for?

  • Search in applications
  • Website search
  • Search in enterprise systems
  • Log analysis
  • Application performance monitoring
  • Infrastructure and container monitoring
  • Analysis and visualisation of geospatial data
  • Security analytics
  • Business analytics

Elasticsearch is a unified search engine of various data.

Elasticsearch receives data from a variety of sources, such as web applications, logs, or infrastructure information. Elasticsearch analyses and converts raw data into a normalised form so that it can be indexed. Subsequently, it is possible to search in them, analyse them and obtain comprehensive overviews and data summaries.

Advanced tools

Elastic Index

Elasticsearch index is an assignment for several elements that are interconnected and are stored as a JSON document. Each of the documents is then associated with a set of keys that characterise it. These keys take the form of numeric or Boolean values, a text string, geolocation, etc.

Elastic Stack (ELK Stack)

Elastic Stack is also referred to as ELK Stack based on the initials of its three components, which are Elasticsearch, Logstash and Kibana. While Elasticsearch works with the acquired data, Logstash provides aggregation and processing of data on the server side.
This makes it possible to receive data from multiple sources simultaneously and enrich it before indexing in Elasticsearch. Kibana, in turn, provides better visualisation and data management. It allows you to create not only common graphs and histograms, but also dynamic infographics or maps with visualisation of geospatial data.

We will assist you on Elasticsearch

We will assist you on Elasticsearch

Need help implementing, setting up, or configuring Elasticsearch or Elastic Stack? Let us know. We use both Elasticsearch and Elastic Stack on a daily basis and can tune it to work exactly as you need it.