Elasticsearch
NewThe search database for AI
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
- Elasticsearch ranks #7 of 30 in Vector Databases with an AI visibility score of 14.3 (SlateIndex, Nov 2, 2026).
- Elasticsearch is most visible on Perplexity (19.1) and least on ChatGPT (11.5).
- AI engines name Elasticsearch in 16 of the 30 Vector Databases buyer prompts SlateIndex tracks.
- github.com is the source AI engines cite most in answers about Elasticsearch, with 17 citations.
About
Company details for Elasticsearch
Elasticsearch is a distributed, RESTful search and analytics engine built on Apache Lucene. It stores structured and unstructured data and supports full-text, vector and hybrid search, plus real-time analytics. It is the core of the Elastic Stack and underpins Elastic's Search, Observability and Security solutions. It can be run on Elastic Cloud Serverless, Elastic Cloud Hosted, or self-managed. It ranks #7 of 30 in Vector Databases on SlateIndex and has a visibility score of 14.3 in the latest weekly run.
Founded in 2012 and headquartered in San Francisco, California, the company employs 1,001–5,000 people. Its differentiator: one search engine that stores every shape of data and runs vector, hybrid and semantic search alongside observability and security workloads.
- Website
- elastic.co
- Categories
- Vector Databases
- Company size
- 1,001–5,000 employees
- Headquarters
- San Francisco, California
- Founded
- 2012
- Company type
- Public company
- Funding
- IPO (NYSE)
- Deployment
- Elastic Cloud Serverless, Elastic Cloud Hosted, or self-managed on premises, in private, hybrid or air-gapped environments.
- Platforms
- AWS, GCP, Azure
- Compliance
- SOC 2 Type II, ISO/IEC 27001, ISO/IEC 27017, ISO/IEC 27018, ISO/IEC 27701, FedRAMP Moderate, FedRAMP High, PCI DSS, HIPAA, CSA STAR
- Support
- Four support tiers depending on Elastic Cloud subscription tier, 99.95% monthly uptime SLA for Platinum and Enterprise tiers
Read from linkedin.com, sec.gov, gartner.com, elastic.co, grokipedia.com, ir.elastic.co · refreshed Nov 2, 2026.
AI visibility
Latest weekly run · Nov 2 · next run Nov 9
Visibility score trend
Weekly runs over the last 60 days, with up to 7 competitors. Click a name to hide or show its line.
Changes appear after the second weekly run in Vector Databases. Pinecone leads the category at 71.8%.
Media
Website and product screenshots for Elasticsearch
AI mentions & citations
Recent answers that name Elasticsearch
What is a vector database and when does a company need one?
A company typically needs a vector database when traditional databases (SQL, NoSQL, or full-text search engines like Elasticsearch) fall short of handling unstructured data or semantic intent.
Best vector database for enterprise
There is no universal winner, but Elasticsearch is the strongest general enterprise choice when you need vector search alongside full-text search, logs, analytics, governance, and flexible deployment.
What are the pros and cons of CrateDB?
It combines the scalability and search capabilities of a NoSQL engine (built on Elasticsearch architecture) with the familiarity of a relational SQL interface.[](https://cratedb.com/academy/fundamentals/why-…
How do companies store and search embeddings without a dedicated tool?
Existing search engines: Elasticsearch and OpenSearch can store dense vectors alongside traditional inverted indexes, enabling hybrid keyword-plus-semantic search.
Where can I sign up for a vector database?
Elastic Cloud Serverless — Create an Elasticsearch Vector Database project with a free 14-day trial.
How do companies store and search embeddings without a dedicated tool?
Use Elasticsearch or OpenSearch
What should a vector database integrate with?
Examples: Elasticsearch, Apache Solr, Algolia.
What are the pros and cons of CrateDB?
Potential vendor/service costs: Managed offerings can simplify operations but should be compared carefully with self-hosting and alternatives such as PostgreSQL, ClickHouse, Elasticsearch, or cloud data warehouses.
Products & features
What Elasticsearch sells
Elasticsearch
Search and analytics engine and vector database with vector, hybrid and semantic search, reranking and RAG support.
Elastic Observability
Logs, metrics, traces and APM in one stack.
Elastic Security
SIEM, endpoint protection and security automation.
Kibana
Shared visualization and management UI across solutions.
Logstash
Server-side data ingestion pipeline.
Beats
Lightweight data shippers.
Elastic Agent
Unified agent for logs, metrics and security data.
Strengths engines cite
- Strongest general enterprise choice for vector search alongside full-text search, logs, and analytics
- Widely deployed, often cited as the most widely deployed vector-capable search engine
- Hybrid keyword-plus-semantic search via dense vectors and inverted indexes
- Suited to consolidated stacks and broader search, logging, analytics, or observability platforms
- Existing infrastructure can be leveraged
Target market & buyers
Notable customers include Tinder, Banco Bradesco, Chainguard, Anyone.com, PSCU, OmniSOC.
| Industry | Primary use case |
|---|---|
| Banking | Real-time CRM search at high event volume |
| Security operations | SIEM, threat detection and managed SOC services |
| Software and IT operations | Logs, metrics and traces observability |
| Consumer apps | Real-time recommendations |
Funding & recent developments
Funding
| Round | Year | Amount |
|---|---|---|
| Series A | 2012 | $10M |
| Series B | 2013 | $24M |
| Series C | 2014 | $70M |
| Series D | 2016 | $58M |
| IPO (NYSE) | 2018 | $252M |
| Latest known round | Total raised |
|---|---|
| IPO (NYSE) | — |
Recent developments
- Oct 2026PartnershipAudi Revolut F1 Team partnership
Multi-year partnership making Elastic the official search and observability supplier from the 2027 season.
- Oct 2026ProductAlertZero AI agents for security operations introduced
Elastic introduced AlertZero, a set of AI agents for security operations, as a technical preview.
- Aug 2026CompanyAcquisition of Deductive AI completed
Elastic completed the acquisition of Deductive AI.
- Jul 2026CompanyChief Product Officer resigns
Chief Product Officer Ken Exner resigned, with his last day on July 17, 2026.
- Jun 2026CompanyRestructuring plan with about 7% job cut
Elastic committed to a restructuring plan with a roughly 7% job cut and $22–25M in charges.
Competitive landscape
How Elasticsearch compares with its top three alternatives
Elasticsearch most often appears alongside PostgreSQL, Pinecone, Weaviate in AI answers.
| Brand | Visibility | Share of voice | vs last week | Starting price |
|---|---|---|---|---|
| Elasticsearch | 14.3% | 5.1% | New | Pricing not available |
| PostgreSQL | 49% | 12.6% | New | Pricing not available |
| Pinecone | 71.8% | 14% | New | Free plan |
| Weaviate | 45.2% | 11.7% | New | Free plan |
| Qdrant | 60.5% | 13.4% | New | Free plan |
What AI answers say
Sentiment and themes from the answers that mention this brand
Positive 30% · Neutral 59% · Mixed 11% of 27 engine answers that mention Elasticsearch
Praised for
- Strongest general enterprise choice for vector search alongside full-text search, logs, and analytics
- Widely deployed, often cited as the most widely deployed vector-capable search engine
- Hybrid keyword-plus-semantic search via dense vectors and inverted indexes
- Suited to consolidated stacks and broader search, logging, analytics, or observability platforms
- Existing infrastructure can be leveraged
Criticised for
- Smaller community and ecosystem than PostgreSQL, MySQL, MongoDB
Cite as: SlateIndex, “Elasticsearch AI visibility profile”, https://slateindex.ai/brand/elasticsearch, data of Nov 2, 2026. Licence: CC BY 4.0.