Why Elasticsearch?

LiteBreeze successfully implements Elasticsearch in many complex projects

Elasticsearch is a readily-scalable enterprise-grade search and analytics engine. It enables users to search, process and store huge amounts of data quickly.

It’s RESTful, and can power extremely fast searches that allow users to gather complex relations and patterns from the data in near real-time. Unlike regular SQL, Elasticsearch comes with Query DSL, which supports full-text search on stored data.

It is more powerful at data aggregations. It can filter within a fraction of the time taken by conventional SQL systems.

Users can build search-filters of varying complexities, search engines, auto-suggests, processing logs, anomaly detection, etc. It also helps ingest structured or unstructured data from multiple sources. It stores this data in a common format to process in a singular fashion.

Our Elasticsearch projects

These are two of our clients. You can browse our other projects here:

  • ActaPublica.se is Sweden's largest document database and research company. They have an archive of around 20 years worth of data and reports. They provide comprehensible information, surveys and compilations to enable in-depth analysis and strategy planning. ActaPublica provides real-time monitoring services as well.

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  • Through this online coaching and e-learning platform, experienced experts share knowledge through telepresence. In live sessions, experts use voice, video call, and screen sharing. This offers a personalized experience to skill seekers. This high-traffic web application has taken many man-hours to develop.

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More information about Elasticsearch

LiteBreeze integrates Elasticsearch as per project requirement

Elasticsearch is coupled with the integrated Kibana visualization and reporting tool, this allows users to visualize complex data and present it in an easily understandable manner.

Elasticsearch, Logstash and Kibana coupled with the tools like Beats is referred to as the ELK stack. Integration with Beats and Logstash, enables users to easily transform source data and load it into your Elasticsearch cluster.

The Elastic cluster is easily scalable and can hold large amounts of data scaling even to Petabytes. It is offered in popular languages like PHP, .NET, Python, Java etc and works well with popular web-frameworks like Laravel.

LiteBreeze has been actively using the ELK stack for the last few years. For example: as a product catalog for a webstore client. It enables search and advanced filtering, text analysis and processing, collects and monitors logs and visualizes the application/infrastructure metrics.

Few of our recent use-cases were:

  1. Storing product catalog and enabling search and advanced filtering on it.
  2. Store document and files content and metadata, creating advanced filtering, retrieval and aggregations on it.
  3. Ingest system logs from different sources and visualize in Kibana for identifying issues.

Many large companies use Elasticsearch for storing and searching their documentation. Airbus is one example. They have two billion blocks of technical documents related to their aircraft.

Elasticsearch allows them to give efficient support to all partners involved in manufacturing and servicing their various airplane models. Searches are made through a modern document search platform.

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