Category: ES|QL
Articles tagged ES|QL
Elasticsearch as one platform: What a second data system really costs
Running search, analytics, metrics, logs, and vector retrieval in five systems costs more than five licenses. Here's what one platform looks like in practice.
One query, three data sources: ES|QL subqueries get FROM, TS and ROW
Filter application logs by live metric behavior and combine indexed data with inline test values. Your filter lists pull from time-series data on the fly, so nothing is hard-coded.
One ES|QL query instead of two: WHERE IN subquery replaces the copy-paste loop in Elasticsearch
ES|QL's WHERE clause can filter by another Elasticsearch subquery's results instead of a static ID list you copied by hand, with nested subqueries, NOT IN and compound conditions built in.
From search to checkout in 20 lines of code: building a 4-stage conversion funnel with OpenTelemetry
Add cart and purchase tracking to your search analytics pipeline and use ES|QL to answer the question every product manager asks: which search queries drive the most revenue?
Elasticsearch ES|QL brings full-text search to data you never indexed
MATCH and TO_TEXT bring full-text search to data you never indexed. Search computed columns, unmapped fields and federated sources in ES|QL.
Prompt to dashboard in under a minute, 5x cheaper: AI dashboards and custom Vega-Lite charts in Kibana
Describe your metrics in natural language and Kibana's AI chat generates ES|QL-backed dashboards and Vega-Lite charts, from scatter plots to conditional formatting and custom tooltips.
Close enough is fast enough: How ES|QL Fast mode makes Kibana dashboards up to 100x faster
Fast mode samples a fraction of the data instead of scanning all of it. This release also brings click-to-filter for ES|QL charts, query-powered controls, and cleaner metric and bar chart layouts.
15 lines of click tracking code that tell you what search logs can't
Three ES|QL queries calculate click-through rate, mean reciprocal rank and click position distribution from your search click data, so you can pinpoint which queries need relevance tuning and where ranking improvements will have the most impact.
How Elasticsearch detects multiple change points in time series with 0.99 recall
ES|QL's CHANGE_POINT command finds structural shifts, variance changes and spikes in any metric in ~1ms, without tuning anything per series.
How to instrument your search API with OpenTelemetry and query it with ES|QL
Add custom attributes to OpenTelemetry spans and run six ES|QL queries that reveal your top searches, zero-result rate and slowest queries.
How to build search analytics on Elastic using OpenTelemetry, no extra pipeline required
How to instrument your search application to use modern Open Telemetry standard to drive insights in to your search and users.
