Get Elasticsearch running for search
Elastic Cloud Serverless projects are autoscaled environments, fully managed by Elastic and available on Elastic Cloud. Availability This functionality is generally available and ready for production usage. Serverless interfaces and procedures might differ from classic Elastic Stack deployments. The Elastic Stack includes Elastic's core products such as Elasticsearch, Kibana, Logstash, and Beats. Availability This functionality is generally available and ready for production usage. Unless stated otherwise on the page, this functionality is available when your Elastic Stack is deployed on Elastic Cloud Hosted, Elastic Cloud Enterprise, Elastic Cloud on Kubernetes, and self-managed environments. This documentation corresponds to the latest patch available for each minor version. If you're not using the latest patch, check the release notes for changes.
Serverless
Generally available
Stack
Generally available
Elasticsearch is at the core of every Elastic deployment type. The deployment type you choose determines who manages the infrastructure, scaling, and upgrades, and how usage is billed. This page briefly introduces the deployment types you can use to get Elasticsearch running quickly, and points you to resources that compare them in detail.
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Choose a deployment and get Elasticsearch running
Get Elasticsearch running in a few minutes.
Elastic Cloud Serverless: Elastic automatically scales and upgrades the project. Projects are versionless, so you always get the latest features.
Serverless has two project types optimized for different search workloads. Choose the one that matches your data and use case:
- Elasticsearch Vector Database project: For most search workloads, this is the recommended option. It is optimized for vector workloads, such as RAG, recommendations, and multimodal search. Sign up for a 14-day free trial.
- Elasticsearch project: If you have logs, events, time series, or telemetry data, choose this project type. Sign up for a 14-day free trial.
Elastic Cloud Hosted: You size, scale, and upgrade the cluster yourself, and you select the hardware profile it runs on. The cluster runs a specific Elastic Stack version. Sign up for a 14-day free trial.
- Local development: Get started quickly with Elasticsearch and Kibana in Docker for local development and testing.
TipThese are the fastest ways to get Elasticsearch running for search. Elastic offers additional deployment types for production workloads on your own infrastructure.
For more detail on the options listed here, and to compare all deployment types across factors like data residency, compliance, feature availability, and infrastructure control, refer to the full list of deployment options and the detailed feature comparison.
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Try a quickstart
Once you have Elasticsearch running, try a quickstart tutorial:
- Elasticsearch vector and full-text search in 10 minutes: Connect a client and run full-text, semantic, and hybrid search. You can follow the examples in Python, TypeScript, PHP, Ruby, C#/.NET, Java, or Go.
- Quickstart: Indexing and search in Elasticsearch: Create an index, add documents, and run a search. This tutorial goes further into indices, including dynamic and explicit mappings.
- Build your first search query with Python: Build a keyword search query with Python.
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Next step
After you have selected and started a deployment, get connected: find your endpoint and create an API key in Get your Elasticsearch endpoint and API key.