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get-started/elasticsearch.md

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The distributed {{es}} architecture enables the following:
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* Horizontal scaling - Add more nodes to increase capacity
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* High availability - Maintained through data replication across nodes to prevent data loss
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* Parallel processing - Queries execute across shards simultaneously to deliver fast performance
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* **Horizontal scaling** —— Add more nodes to increase capacity
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* **High availability** —— Maintained through data replication across nodes to prevent data loss
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* **Parallel processing** —— Queries execute across shards simultaneously to deliver fast performance
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### Near real-time indexing [elasticsearch-near-real-time-indexing]
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Vector capabilities enable the following:
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* Semantic search - Find content based on meaning rather than exact keywords
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* Hybrid search - Combine keyword and vector-based search results for greater accuracy
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* Retrieval-augmented generation (RAG) systems - Provide relevant context to large language models
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* **Semantic search** —— Find content based on meaning rather than exact keywords
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* **Hybrid search** —— Combine keyword and vector-based search results for greater accuracy
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* **Retrieval-augmented generation (RAG) systems** —— Provide relevant context to large language models
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## How {{es}} works [how-elasticsearch-works]
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### Full-text and hybrid search [elasticsearch-full-text-hybrid-search]
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* E-commerce product catalogs - Fast product discovery with filters, facets, and autocomplete
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* Enterprise knowledge bases - Search across documents, wikis, and databases with permission controls
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* Content platforms - Search articles, videos, and user-generated content by relevance
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* **E-commerce product catalogs** —— Fast product discovery with filters, facets, and autocomplete
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* **Enterprise knowledge bases** —— Search across documents, wikis, and databases with permission controls
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* **Content platforms** —— Search articles, videos, and user-generated content by relevance
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### AI-powered applications [elasticsearch-ai-powered-applications]
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* Semantic search - Find documents by meaning using vector embeddings from models like BERT or OpenAI
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* Chatbots and RAG systems - Retrieve relevant context from knowledge bases to enhance LLM responses
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* Recommendation engines - Surface similar items based on vector similarity
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* **Semantic search** —— Find documents by meaning using vector embeddings from models like BERT or OpenAI
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* **Chatbots and RAG systems** —— Retrieve relevant context from knowledge bases to enhance LLM responses
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* **Recommendation engines** —— Surface similar items based on vector similarity
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### Geospatial search [elasticsearch-geospatial-search]
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* Location-based services - Find nearby restaurants, stores, or services
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* Delivery routing - Optimize routes based on geographic data
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* Geofencing - Trigger actions when users enter specific areas
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* **Location-based services** —— Find nearby restaurants, stores, or services
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* **Delivery routing** —— Optimize routes based on geographic data
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* **Geofencing** —— Trigger actions when users enter specific areas
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### Analytics and monitoring [elasticsearch-analytics-monitoring]
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* Log analytics - Centralize and analyze application and system logs
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* Security analytics - Detect threats and anomalies in security events
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* Business metrics - Analyze user behavior, sales trends, and KPIs
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* **Log analytics** —— Centralize and analyze application and system logs
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* **Security analytics** —— Detect threats and anomalies in security events
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* **Business metrics** —— Analyze user behavior, sales trends, and KPIs
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## When to use {{es}} [when-to-use-elasticsearch]
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### Deployment options [elasticsearch-deployment-options]
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* **[{{serverless-full}}](/deploy-manage/deploy/elastic-cloud/serverless.md)** - Fully managed, auto-scaling deployment, which is recommended for new projects
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* **[{{ech}}](/deploy-manage/deploy/elastic-cloud/cloud-hosted.md)** - Managed {{es}} with more configuration control
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* **[Self-managed](/deploy-manage/deploy/self-managed.md)** - Install and operate {{es}} yourself, which requires expertise
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{{es}} offers flexible deployment options to match your organization requirements and level of operational control.
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| Option | Description |
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| ----- | ----- |
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| **[{{serverless-full}}](/deploy-manage/deploy/elastic-cloud/serverless.md)** | Fully managed, auto-scaling deployment. Recommended for new projects. |
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| **[{{ech}}](/deploy-manage/deploy/elastic-cloud/cloud-hosted.md)** | Managed {{es}} with more configuration control. |
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| **[Self-managed](/deploy-manage/deploy/self-managed.md)** | Install and operate {{es}} yourself. Requires expertise. |
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### Cluster sizing [elasticsearch-cluster-sizing]
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* Small deployments - 3-5 nodes for development and small production use cases
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* Medium deployments - 10-20 nodes for moderate data volumes and query loads
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* Large deployments - 50 or more nodes for high-volume production systems
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To make sure your {{es}} deployment performs efficiently and scales with your data and query demands, use the right cluster size.
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| Deployment size | Cluster size |
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| ----- | ----- |
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| **Small** | 3-5 nodes for development and small production use cases. |
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| **Medium** | 10-20 nodes for moderate data volumes and query loads. |
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| **Large** | 50 or more nodes for high-volume production systems. |
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### Data modeling best practices [elasticsearch-data-modeling-best-practices]
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get-started/toc.yml

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project: 'Get started'
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toc:
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- file: index.md
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- file: introduction.md
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- file: elasticsearch.md
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- file: introduction.md
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- file: the-stack.md
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- file: deployment-options.md
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- file: versioning-availability.md

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