Elasticsearch as a Time Series Data Store
Blog post from Elastic
Felix Barnsteiner discusses the suitability of Elasticsearch as a time series database for performance monitoring, specifically for the open-source tool stagemonitor, which needed a replacement for the aging Graphite TSDB. He highlights Elasticsearch's ease of installation, scalability, and strong visualization capabilities, especially when paired with Kibana, making it an attractive choice despite initial doubts about its aptitude for time series data. Barnsteiner references a CERN performance comparison that favored Elasticsearch over InfluxDB and OpenTSDB, further supporting its use. Essential practices such as defining mappings, disabling source for metric documents, and employing doc_values are emphasized to optimize storage and performance, while aggressive optimizations like using index "no" for metric values and force merging indices are discussed for long-term data management. Barnsteiner also outlines improvements in Elasticsearch 2.0, such as pipeline aggregations and default doc_values, which enhance its flexibility for time series data applications.
No tracked trend matches for this post yet.
Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.