Elasticsearch 9.4 - the world's leading distributed search and analytics engine powering full-text search, log observability, and AI-driven semantic retrieval at any scale.
Elasticsearch is the world's most widely adopted distributed search and analytics engine, built on Apache Lucene and delivered via a schema-free RESTful JSON API. Version 9.4 (May 2026) brings native semantic search, ES|QL Views, vector kNN acceleration, and LogsDB storage compression — making it the single platform teams reach for across full-text search, log observability, and AI-powered retrieval.
Inverted index and HNSW graph structures return results within milliseconds across billions of documents, with index changes visible in under one second.
Automatic shard allocation across nodes means you add capacity simply by joining new nodes — no application changes. It handles petabyte-scale datasets in production.
Dense vector (kNN) and sparse vector (ELSER) fields enable semantic search natively alongside BM25 keyword matching — no external vector database needed.
Bucket, metric, pipeline, and matrix aggregations run directly against indexed data, powering dashboards and alerts without separate OLAP infrastructure.
TLS encryption, role-based access control, field- and document-level security, and audit logging have been included free since Elasticsearch 7.1.
2,400+ open-source contributors, official clients for every major language, and seamless integration with Kibana, Logstash, Beats, OpenTelemetry, and Kafka.
Data flows in as JSON, is analysed and indexed, then served back through keyword, vector, or hybrid queries — all across a self-healing cluster of shards and replicas:
From ingest to answer — the Elasticsearch data path
Documents are submitted as JSON over HTTP. Elasticsearch applies the configured mapping — field types, analyzers, tokenizers — builds an inverted index for text fields, and makes documents searchable within roughly one second. Ingest pipelines with built-in processors (grok, enrich, script) transform and enrich data at write time. LogsDB mode reduces log storage by up to 65% via synthetic source and columnar compression.
The Query DSL exposes hundreds of query types — match, multi_match, bool, term, range, geo_distance, and percolate. ES|QL, now with Views support in 9.x, provides a SQL-like pipe syntax optimised for log analytics and exploration directly in the engine. Relevance uses BM25 by default and can be boosted with function_score or rank_feature queries.
Each index is divided into primary shards and one or more replicas for fault tolerance. Shard allocation is handled automatically by the raft-based cluster coordinator, and a primary-shard failure triggers automatic promotion of a replica within seconds. Cross-cluster replication (CCR) and cross-cluster search (CCS) support multi-region and multi-cloud topologies with no application-layer plumbing.
Dense vector fields (up to 4,096 dimensions) use HNSW graphs for approximate k-nearest-neighbour search, and Elasticsearch 9.x delivers roughly 30% faster HNSW queries versus 8.8 benchmarks. ELSER provides out-of-the-box semantic retrieval with no externally managed embedding models, and hybrid search with Reciprocal Rank Fusion (RRF) combines keyword and vector scores in a single request.
Cumulative downloads have climbed steadily past 1.4 billion, reflecting how deeply Elasticsearch has embedded itself across search, observability, and AI workloads.
Elasticsearch cumulative downloads (billions) — 2019 to 2025
| Capability | Elasticsearch 9.x | OpenSearch 2.x | Apache Solr 9.x | Algolia |
|---|---|---|---|---|
| Full-text search | ✓ | ✓ | ✓ | ✓ |
| Native vector / kNN search | ✓ | ✓ | ✗ | Partial |
| Semantic search (built-in model) | ✓ ELSER | Partial | ✗ | ✗ |
| Log & observability at scale | ✓ LogsDB | Partial | ✗ | ✗ |
| Aggregations / analytics | ✓ | ✓ | Limited | ✗ |
| ES|QL / SQL interface | ✓ | Partial (PPL) | ✗ | ✗ |
| Self-hosted & cloud options | ✓ | ✓ | ✓ | Cloud only |
| SIEM / security analytics | ✓ | Partial | ✗ | ✗ |
Faceted filtering, synonym dictionaries, typo-tolerant fuzzy matching, and relevance tuning drive product discovery and personalised ranking at catalogue scale.
Centralised ingestion of application, infrastructure, and security logs via Elastic Agent or Beats. LogsDB cuts storage costs by up to 65% while retaining full query capability.
Real-time correlation of security events, threat-intelligence enrichment, and ML-based anomaly detection power SIEM and SOAR workflows in regulated industries.
Unified search across SharePoint, Confluence, Salesforce, and internal databases surfaces the right document or answer from any authoritative source in milliseconds.
Hybrid BM25 + kNN retrieval feeds grounded context into LLM pipelines, reducing hallucinations and ensuring responses are backed by your proprietary data.
Geo-point and geo-shape fields enable proximity search, bounding-box filtering, and geospatial aggregations for logistics, mapping, and location-aware applications.
We audit your data sources, query patterns, and SLAs to size the cluster and shape the index model correctly.
We set up mappings, ingest pipelines, and the client library, connecting Elasticsearch to your application stack.
We tune relevance, add ILM tiering, and build monitoring dashboards so search stays fast and cost-efficient.
As data and traffic grow, we add nodes and replicas with zero downtime and no application changes.
Beyond the engineering, Elasticsearch with ELIVTECH delivers outcomes your whole organisation can feel:
Fast, typo-tolerant, relevant search turns browsing into buying — users reach the right product or answer in milliseconds instead of giving up.
LogsDB compression cuts log storage by up to 65%, so you keep more history for compliance and troubleshooting while spending less on infrastructure.
Real-time dashboards and anomaly detection surface issues and threats early, protecting revenue, uptime, and reputation.
Semantic and hybrid retrieval let AI assistants answer from your own trusted content, making generative features accurate and safe to ship.
Our engineers ship production-grade Elasticsearch solutions. Let's scope yours.
Talk to an engineer