How Elasticsearch cuts time-series storage by 34% with synthetic _id and bloom filters
Learn how synthetic _id uses bloom filters to cut time-series storage by 34% while maintaining full API compatibility.
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Learn how synthetic _id uses bloom filters to cut time-series storage by 34% while maintaining full API compatibility.
How we brought Elasticsearch's native SIMD scoring engine to serverless, and why serverless is where vector search innovation happens next.
See how asymmetric quantization cuts DiskBBQ query quantization overhead from about 20% to 4% with little recall impact.
Jina-VLM is a 2.4B open multilingual VLM leading VQA benchmarks across 29 languages. Plus: five days of ICLR 2026 takeaways on RLVR, sparse embeddings and retrieval.
Find out how Kibana uses continuous polling and browser-side HTTP/2 detection to cut dashboard load times by up to 25%, with automatic fallback on HTTP/1.
ES|QL now supports approximate query execution. Add one line to your queries, and get results orders of magnitude faster, with built-in confidence intervals that tell you exactly how much to trust them.
Recalibrate your mental model for time series queries: learn why FROM can produce inaccurate results for metrics, how TS fixes that, and when to use each command.
Learn how to optimize ecommerce search using margin and popularity boosting. This blog explains how a governed control plane treats economic optimization in Elasticsearch.
Query Elasticsearch directly from Prometheus-compatible clients via native PromQL, discovery, and metadata endpoints. Send data to Elasticsearch with Prometheus Remote Write.
Query any percentile at any time. Elasticsearch natively stores OTel exponential histograms and lets you analyze distributions in ES|QL without fixed buckets or lossy conversions.
ES|QL subqueries give each data source its own pipeline and filters, eliminating CASE chains, restoring predicate pushdown, and making multi-index queries extensible by design.
Learn how to build a multi-tier retrieval strategy used to execute ecommerce governed search plans and improve recall management. We'll cover how to orchestrate semantic matching while maintaining stable results, facets, and pagination.
With ES|QL views, you only need one query for multiple dashboards. Define it once and let Elasticsearch keep everything in sync.
Learn how to use the Elasticsearch percolator to implement search governance. In this blog, we outline the patterns needed to create a governed policy engine in production and create a controlled retrieval strategy.
Learn how to measure and improve search recall in Elasticsearch by combining BM25 lexical search with Jina AI vector embeddings, using the rank_eval API to validate the improvement with real numbers.
How to build a governed control plane for ecommerce that composes conflicting search policies into a single execution plan (without code changes).