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Episode 33 - Considering Elasticsearch as a Time Series Database
Manage episode 178633286 series 1163484
Content provided by Breandan Dezendorf, Ken Mink, Jack Neely, and Jarod Watkins. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Breandan Dezendorf, Ken Mink, Jack Neely, and Jarod Watkins or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Where we discuss using Elasticsearch (along with Kibana, Timelion and Kafka) as a Timeseries Database (TSDB). It has several drawbacks over traditional timeseries storage engines, mostly in storage efficiency, but has other unique attributes that may overcome these drawbacks in the right use case.
Comments for the episode are welcome - at the bottom of the show notes for the episode there is a Disqus setup, or you can email us at feedback@operations.fm
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138 episodes
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Manage episode 178633286 series 1163484
Content provided by Breandan Dezendorf, Ken Mink, Jack Neely, and Jarod Watkins. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Breandan Dezendorf, Ken Mink, Jack Neely, and Jarod Watkins or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Where we discuss using Elasticsearch (along with Kibana, Timelion and Kafka) as a Timeseries Database (TSDB). It has several drawbacks over traditional timeseries storage engines, mostly in storage efficiency, but has other unique attributes that may overcome these drawbacks in the right use case.
Comments for the episode are welcome - at the bottom of the show notes for the episode there is a Disqus setup, or you can email us at feedback@operations.fm
Links for Episode 33:
138 episodes
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