Blogs
Developer insights and practical how-to articles from our experts to inspire and empower your search experience.
98.9% faster queries, 4x more indexing throughput: a systematic Elasticsearch performance diagnosis
Use AutoOps, the Profile API and ES Rally together to find cluster hotspots, slow queries and index bottlenecks, with real benchmarks showing a 98.9% latency cut and 4x indexing gain.
How BBQ shrinks Jina v5 embeddings by 29x without losing recall in Elasticsearch
A hands-on test comparing BBQ and float32 vector indices in Elasticsearch, measuring memory, disk and recall@10 across five languages.
Why Elasticsearch is becoming a columnar database
Elasticsearch is becoming a first-class columnar database. Columnar Mode ships in 9.5, storing data once alongside the existing modes and cutting storage footprints while speeding up analytical 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.
Short queries, formal documents: how HyDE improved semantic search precision by 50% in Elasticsearch
HyDE boosts semantic search precision and recall by 50% on short queries. Here's how to implement it in Elasticsearch with the Inference API and semantic_text.
Your compliance posture just got an upgrade: Elasticsearch now supports FIPS 140-3
Elastic 9.4 brings FIPS 140-3 support for Elasticsearch and Kibana to GA. Here's what changes for federal, defense and regulated deployments, and how to migrate from 140-2.
Who grades the grader? LLM-as-a-Judge inside Elasticsearch Workflows
Find out if your RAG agent is ready to ship. Score it on correctness, faithfulness and retrieval quality using only Elasticsearch Workflows and two Claude models.
Follow the money: tracing laundering networks with ES|QL and cross-cluster search
The data model, cross-cluster architecture and five ES|QL queries that power mule detection and laundering network tracing, built from infrastructure most financial institutions already run.
A simdvec deep-dive: How Elasticsearch uses neural-net and video-codec CPU instructions for vector search
Four ways Elasticsearch's vector search engine reuses neural-network, video-codec and cryptography CPU instructions for up to 6x speedups; with the math, the failed attempts and the benchmarks.
One command. Natural language. Your Elasticsearch data, straight to the terminal.
Query your Elasticsearch data from the terminal in plain English. The official Elastic GitHub Copilot CLI plugin generates and runs ES|QL queries against your cluster. No Kibana, no manual syntax.
Piping Hot: Bringing ES|QL to Your Grafana Dashboards Using the Elasticsearch Plugin
You can now write ES|QL queries in Grafana with the Elasticsearch plugin. Learn how to enable it and write pipe-based queries directly in the Grafana UI.
