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Exact kNN on 1M vectors: ~10 QPS
HNSW on the same dataset: ~1000 QPS
This is because HNSW builds a layered graph:
shortcuts at the top, all vectors at the bottom.
A query enters at the top layer, finds the closest node, uses it as the entry point for the layer below, and repeats until it reaches a tight local search at layer 0.
It also let you tune your indexing speed vs query speed vs recall, so you can get the index that suits your needs.
At @Elastic, we just took a massive leap. 🚀
Our new columnar metrics engine is 30x faster than Prometheus. Better performance, lower TCO, and all your telemetry in one place.
Proud of the team for this milestone!
Details here: https://t.co/yIAd7SL1hz
30x faster than Prometheus on gauge averages sounds like a typo. It's not.
Elasticsearch 9.4 rebuilt TSDS and ES|QL into a fully columnar metrics engine. Vectorized time series aggregations, zero-copy decoding, doc value skippers replacing inverted indices.
The result at 1.4M time series: queries that took Prometheus 30+ seconds finish in under 2.
semantic_text now defaults to jina-embeddings-v5-text on Elastic Inference Service.
Multilingual semantic search. Zero extra configuration. Define the field, index your data, search.
Query in English: "comfortable headphones for long flights"
A French review ranked above the English one, because "très confortable pour les longs trajets en avion" was a closer semantic match than the English review, which split its focus across battery life and noise cancellation.
Oubliez le RAG basique. Comment gère-t-on vraiment la mémoire d'un agent conversationnel en prod ? 🛠️
RDV chez La HSC avec @IvanMonnier & Louis Jourdain (ChapsVision). Architecture multi-index & observabilité au programme.
👉 https://t.co/fceU0summh
Elastic is heading to KubeCon Amsterdam 2026 🇳🇱
Visit booth #980 to see how we’re building OpenTelemetry to simplify ingestion, reduce pipeline complexity, and deliver consistent observability across metrics, logs, and traces with a focus on agentic observability.
Come see the demos and meet the team: https://t.co/Wua0YoNxqo
APT confirmation used to take hours. Now it takes 4 minutes.
Attack Discovery correlates alerts into a single narrative.
A workflow triggers the agent.
The agent:
• Looks up the hash on VirusTotal
• Runs ES|QL queries across your logs
• Finds the on-call analyst
• Creates a case
• Opens a Slack incident channel
All before you read the threat intel report.
Forcing LLMs to follow a strict schema is hard.
Build reliable AI agents using structured outputs
This guide shows how to ground your agents using data contracts to ensure valid responses every time.
What you will learn:
• How to define your schema for agentic workflows
• Using the Elasticsearch inference API for data extraction
• Implementing validation
Stop guessing if your agent will return valid JSON.
Et voilà ! So proud to reach the 100th meetup milestone for the @ElasticFR 🇫🇷 community.
A huge thank you to our speakers, sponsors, and community members for making every event a success! ❤️
📺 Watch here: https://t.co/AEeStTI05E
What are you going to eat today? For the final advent calendar gift of the year, @PiotrPrz shares a simple 3-step script to get the healthiest possible food, whatever language you are using, thanks to our OOTB JINA model: https://t.co/A6VinPzRD6
Quelle année 2025 les amis ! Et pour bien commencer 2026, nous fêterons notre 100ème meetup #Elasticsearch chez @BNPParibas avec la présence notamment de @kimchy. 🔎 https://t.co/FMhyJSdBoQ
Bonnes fêtes de fin d'année ! 🎄🎅🏼🎁
We have added a new and interesting retriever! The `diversify` retriever reduces the result set from another retriever by applying a diversification strategy to the top-N results, helping prevent similar documents from dominating the top results.
Discover this trick and more with the Advent Calendar day 6: https://t.co/XgUvEwmeLt
Bonus point for our French community, you can read it in French here: https://t.co/3228sF6uBI
📣 Cette année, nous lançons à nouveau le calendrier de l'Avent. Et @Anaethelion nous régale avec son article, en français ! 🇫🇷
🔗 https://t.co/4S9q0pHYQe
The Elastic Advent Calendar is back again this year! Let's start the first day with @anaethelion, who is offering his `--help` to Santa: https://t.co/MmPMuveQvp
#CLI#Elasticsearch
🎥 Meetup ElasticFR 98 : Analyse de données interactive : la rencontre de ES|QL, @ApacheArrow et #Pandas par @bluxte d'@elastic ⤵️
https://t.co/VtZVbJ7N2E