Map Elasticsearch Index Mappings to a Visual Diagram

Connect DbSchema to Elasticsearch and turn the live schema into an editable visual model: explore relationships in interactive ER diagrams, plan changes on the canvas, and generate reviewed SQL scripts for deployment.

The workflow is designed for visual modeling, schema documentation, and deployment — keep an offline model in Git, collaborate across teams, and publish documentation that developers, analysts, and stakeholders can navigate in minutes.

Download DbSchema See Elasticsearch Features Download Elasticsearch JDBC Driver · All drivers

What happens after you download?

Get to your first Elasticsearch schema diagram in minutes. No account, no credit card.

Install in minutes

Download the installer for Windows, macOS, or Linux and launch DbSchema. No signup required.

Connect to Elasticsearch or open a sample

Reverse engineer an existing Elasticsearch database or open a sample model to explore tables, relationships, and indexes.

Design, document, and deploy

Edit schema visually, generate documentation, and prepare reviewed migration scripts for safer releases.

Get Started Free

Elasticsearch stores documents in indices, and each index has a mapping that defines field names, data types, analyzer configurations, and nested object structures. While Elasticsearch is primarily a search engine, its SQL interface — available from the Basic license tier upward — allows standard SQL queries against index data. DbSchema treats each Elasticsearch index as a table, visualizes field mappings as a schema diagram, and provides SQL and data exploration tools for Elasticsearch environments.

Exploring Elasticsearch Index Mappings and Field Types

Elasticsearch field types — keyword, text, nested, geo_point, dense_vector, and others — determine how documents are indexed and queried. DbSchema reads the mapping from the Elasticsearch REST API and displays each index's field structure, including nested object hierarchies, giving engineers a clear picture of the data model without reading raw mapping JSON.

Download DbSchema Free See Elasticsearch Features

Browsing Elasticsearch index field types and mapping structure in DbSchema

Browsing Elasticsearch Document Data

The DbSchema data explorer fetches documents from Elasticsearch indices and displays them in a tabular format. You can apply field filters to narrow the result set, paginate through large indices, and inspect individual field values — all without writing DSL queries or using the Kibana Discover interface.

Browsing Elasticsearch index document data in DbSchema's data explorer

Schema Documentation for Elasticsearch Indices

DbSchema generates HTML documentation from the Elasticsearch mapping, capturing index names, field types, analyzer assignments, and nested structures as human-readable reference material. For teams managing dozens of indices across environments, this documentation provides an accessible overview of the full data model without requiring Elasticsearch API knowledge.

How to Connect DbSchema to Elasticsearch

Reaching a live Elasticsearch index diagram involves the following steps:

Install DbSchema — the desktop app is free to download for Windows, macOS, and Linux.
Start a new connection, choose Elasticsearch, and register the Elasticsearch JDBC driver from Elastic's download page.
Enter the host and default HTTP port 9200, matching the JDBC URL jdbc:es://http://host:9200. The Elasticsearch SQL feature must be enabled — it ships in the Basic license tier and above with no extra configuration.
For Elasticsearch Service on Elastic Cloud, use the HTTPS cluster endpoint URL instead and supply your API key as the password.
Connect — DbSchema reads the index mappings and renders the field structure as a diagram.

Self-signed certificates require adding the Elasticsearch CA certificate to the Java truststore before connecting.

What DbSchema Adds to an Elasticsearch Workflow

Mapping visualization — view nested field hierarchies and analyzer assignments as a schema diagram instead of raw JSON.
SQL query access — run Elasticsearch SQL queries from the built-in editor without learning the Query DSL.
Document browsing — explore index contents in a tabular data explorer with column filtering and pagination.
Index documentation — generate HTML reference documentation covering all index mappings for team knowledge sharing.
Elastic Cloud support — connect to cloud-hosted Elasticsearch clusters using API key authentication over HTTPS.

Instead of parsing raw mapping JSON, see every index's field hierarchy on one diagram. Download DbSchema for free and browse your Elasticsearch mappings visually today.

Frequently asked questions

Yes. DbSchema connects using the Elasticsearch JDBC driver, treats each index as a table, and visualizes field mappings — including nested object hierarchies — as a schema diagram.

The default HTTP port is 9200, matching the JDBC URL format jdbc:es://http://host:9200.

The Elasticsearch SQL feature is included from the Basic license tier upward with no extra configuration, so DbSchema's SQL editor works against it out of the box.

Teams working with Elasticsearch often use these engines too. Explore dedicated guides and JDBC setup for each.