What are some use cases for using elasticsearch versus standard sql queries? -

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i'm getting started elasticsearch , 1 of main use cases i've seen it's scalability searches on large data sets, besides when want use on creating sql queries traditional rdms?

there 2 primary elasticsearch use cases:

  1. text search

you want elasticsearch when you're doing lot of text search, traditional rdbms databases not performing (poor configuration, acts black-box, poor performance). elasticsearch highly customizable, extendable through plugins. can build robust search without knowledge quite fast.

  1. logging , analysis

another edge case lot people use elasticsearch store logs various sources (to centralize them), can analyze them , make sense out of it. in case, kibana becomes handy. lets connect elasticsearch cluster , create visualisations straight away. instance, loggly built using elasticsearch , kibana.

keep in mind, wouldn't want use elasticsearch primary data storage. reasons here: how reliable elasticsearch primary datastore against factors write loss, data availability

update

i felt second part no longer edgy, it's elastic company has been doing in past year. current devops movement, ci/cd pipelines, increasing amount of metrics various sources, elk became defacto choice infrastructure monitoring, it's no longer distributed restful text-search engine. has amazing set of products:

  • logstash (tons of data inputs)
  • beats
    • filebeat
    • metricbeat
    • packetbeat
    • winlogbeat
  • kibana
    • graph
    • timelion
  • x-pack (premium)
    • alerts
    • reporting
    • security
    • machine learning
    • cross data center metrics

an ecosystem, built community, growing around elk stack expands current features, few of them worth mentioning:

  • elastalert
  • shield guard

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