Uses Google Elasticsearch
What is Elasticsearch?
Elasticsearch is fast. Since Elasticsearch is based on Lucene, it can play its trump cards especially with full-text searches. Elasticsearch is also a near-real-time search engine: the time between indexing a document and finding the document through the search is very short - usually only a second. This makes Elasticsearch particularly suitable for use cases in which time plays a role, such as security analytics and infrastructure monitoring.
Elasticsearch is naturally distributed. The documents saved in Elasticsearch are stored in different containers, the so-called Shards, which are duplicated so that redundant copies are available in the event of a hardware failure. The distributed nature of Elasticsearch makes it possible to scale Elasticsearch to hundreds (or even thousands) of servers and process data petabyte by petabyte.
Elasticsearch has a variety of features. In addition to its speed, scalability and resilience, Elasticsearch has a number of powerful built-in functions that make it even more efficient to store and search for data. This includes, for example, data rollups and index lifecycle management.
The Elastic Stack makes it easy to ingest, visualize, and report on data. Thanks to the Beats and Logstash integrations, data can be easily processed before it is indexed in Elasticsearch. And Kibana offers real-time visualization of Elasticsearch data as well as functions for quick access to APM data, log data and infrastructure metrics.
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