Announcing DataBrain's OpenSearch Integration: Search and Log Analytics in Your Embedded Dashboards

DataBrain now supports OpenSearch as a native data source. Build dashboards and metrics from your OpenSearch indices—log analytics, application metrics, and search data—alongside your existing data sources, with the same filters, drill-downs, and white-label embeds you use everywhere else.

February 2026

Many teams run OpenSearch (or Amazon OpenSearch Service) for logs, search, and observability. Until now, turning that data into customer-facing or internal dashboards meant either exporting to a warehouse, building custom UIs, or juggling multiple tools. Today we're announcing native OpenSearch support in DataBrain: add OpenSearch as a data source, build metrics and dashboards from your indices, and embed them in your product with the same semantic layer, row-level security, and charting you already use for PostgreSQL, Snowflake, or ClickHouse.

OpenSearch is the open-source, vendor-neutral fork of Elasticsearch—widely used for full-text search, log analytics, and APM-style data. With DataBrain's OpenSearch integration, that data becomes first-class in your embedded analytics stack: one place for business metrics, logs, and search analytics. For how OpenSearch fits alongside other databases (PostgreSQL, ClickHouse, warehouses) in your embedded analytics architecture, see How to Choose Databases for Embedded Analytics.

Why OpenSearch + Embedded Analytics

One Platform for Business and Operational Data

Teams often have transactional or analytical data in a warehouse (PostgreSQL, Snowflake, BigQuery) and logs, events, or search data in OpenSearch. Splitting reporting across tools creates fragmented experiences and duplicate effort.

With OpenSearch as a DataBrain data source you can:

• Unify in one UI — Dashboards that combine warehouse metrics with OpenSearch-backed log counts, error rates, or search KPIs.
• Reuse the same patterns — Filters, drill-downs, RBAC, and white-label embeds work for OpenSearch-backed metrics like any other source.
• Ship faster — No ETL from OpenSearch to a warehouse just to build a dashboard; query OpenSearch directly from DataBrain.

Use Cases That Fit OpenSearch as a Source

• Log and observability analytics — Error rates by service, request volume by endpoint, log volume over time, embedded in your app or ops portal.
• Search analytics — Queries per day, no-result rate, top queries, click-through from search to conversion, in the same dashboards as business metrics.
• Application and event data — Event counts, funnels, or behavioral metrics stored in OpenSearch, visualized and filtered with DataBrain's semantic layer and RLS.

Open Source, No Licensing Lock-In

OpenSearch is the Apache-2.0-licensed fork of Elasticsearch. If you've standardized on OpenSearch (or Amazon OpenSearch Service) to avoid Elastic's licensing, DataBrain's integration keeps your analytics on that same stack—no need to introduce another vendor for dashboards.

How the Integration Works

1. Add OpenSearch as a data source in DataBrain: connection URL, authentication (e.g. basic auth), and optional SSL. DataBrain supports self-managed OpenSearch and OpenSearch Cloud (or Amazon OpenSearch Service with the same API).
2. Schema discovery — DataBrain discovers your indices and fields so you can build metrics from them in the same way you do for SQL sources.
3. Build metrics and dashboards — Use DataBrain's metric builder, filters, and 50+ chart types. OpenSearch-backed metrics can sit alongside metrics from PostgreSQL, ClickHouse, Snowflake, and others in the same dashboard.
4. Embed and govern — Row-level security, column-level security, and tenant context apply to OpenSearch-backed metrics. Embed dashboards in your product with your branding and access controls.

Data flows: Your app or users → DataBrain → OpenSearch. DataBrain translates metric and filter logic into OpenSearch queries and returns aggregated results for charts and tables. Underlying data download (e.g. CSV export) is supported for OpenSearch-backed metrics.

Getting Started in 4 Steps

1. Prepare OpenSearch

• Ensure your OpenSearch cluster (self-managed or OpenSearch Cloud / Amazon OpenSearch Service) is running and reachable.
• Enable SSL/TLS if you need encrypted connections.
• Create a user with read access to the indices you want to use in DataBrain (no write required).
• Whitelist DataBrain's IP (or your self-hosted DataBrain API) so it can reach OpenSearch. See Allow access to our IP.

2. Add OpenSearch in DataBrain

1. In DataBrain, go to Data Sources → Add Data Source.
2. Select OpenSearch.
3. Enter: Integration name, Server type (self-managed or OpenSearch Cloud), Connection details, Authentication (if required).
4. Use Check Connection to verify connectivity, then save.

3. Build Metrics and Dashboards

DataBrain will discover indices and fields. Create metrics from your OpenSearch data using the same metric builder and chart types you use for other sources. Add dashboard filters, drill-downs, and merge multiple metrics (including from other data sources) on one dashboard.

4. Embed or Share

Use DataBrain's embed SDK or API to show dashboards in your product, with your branding and access rules.

Setup time: about 15–20 minutes for a first connected source and a sample dashboard.

For step-by-step connection details, authentication options, and troubleshooting, see the OpenSearch data source guide in the DataBrain docs.

Key Benefits

BenefitDescriptionSingle analytics layerLogs, search, and business data in one place—one set of dashboards, filters, and embeds.No ETL for dashboardsQuery OpenSearch directly; no need to sync logs or events to a warehouse just to visualize them.Same governanceRLS, CLS, and multi-tenancy work for OpenSearch-backed metrics like any other source.Open source stackStays on OpenSearch (Apache 2.0); no Elastic licensing for your analytics layer.Multi-datasource dashboardsCombine OpenSearch with PostgreSQL, ClickHouse, Snowflake, and more in the same view.

Example: Log Analytics and Business Metrics in One Dashboard

Scenario: Your product stores business events in PostgreSQL and application logs in OpenSearch. You want one embedded "Product health" dashboard for customers: revenue and signups (PostgreSQL) plus error rate and request volume (OpenSearch).

1. Add PostgreSQL and OpenSearch as data sources in DataBrain.
2. Create metrics: "Revenue (MTD)" and "Signups" from PostgreSQL; "Error count by service" and "Requests per hour" from OpenSearch.
3. Build one dashboard with all four metrics, shared filters (e.g. date range, environment), and drill-downs.
4. Embed the dashboard in your customer portal with row-level security so each customer sees only their data.

No log ETL, no separate log UI—one DataBrain dashboard for both business and operational data.

Frequently Asked Questions

What is OpenSearch and how is it different from Elasticsearch?

OpenSearch is the open-source (Apache 2.0) fork of Elasticsearch, maintained by the OpenSearch project and used by AWS (Amazon OpenSearch Service) and others. It offers the same core search and analytics APIs. DataBrain connects to OpenSearch via its standard API; if you run Elasticsearch, we support Elasticsearch as a separate data source.

Does this work with Amazon OpenSearch Service?

Yes. Amazon OpenSearch Service is compatible with the OpenSearch API. Add it in DataBrain as OpenSearch with the appropriate endpoint, authentication, and IP/security group access so DataBrain can reach your domain.

Do I need to sync OpenSearch data to a data warehouse?

No. DataBrain queries OpenSearch directly for metrics and dashboards. You can still use a warehouse for other use cases; OpenSearch in DataBrain is for building visualizations and embeds without an extra ETL step.

What authentication does DataBrain support for OpenSearch?

Basic authentication (username and password) is supported. The connection can use SSL/TLS. For exact fields and options, see the OpenSearch connection guide.

Can I mix OpenSearch with other data sources on the same dashboard?

Yes. DataBrain supports multi-datasource dashboards. You can combine metrics from OpenSearch, PostgreSQL, ClickHouse, Snowflake, and other supported sources on one dashboard with shared filters and drill-downs.

Is underlying data download (CSV, etc.) supported for OpenSearch metrics?

Yes. You can export underlying data for OpenSearch-backed metrics (e.g. CSV download), subject to your DataBrain and OpenSearch permissions.

Next Steps

• Connect OpenSearch — Follow the OpenSearch data source guide to add your first source and run a connection check.
• Explore other sources — See Connecting data sources to DataBrain for the full list (PostgreSQL, ClickHouse, Trino, Athena, Elasticsearch, and more).
• Need help? — Contact us or talk to our team for architecture guidance or multi-source dashboard design.

Summary

• OpenSearch is now a native DataBrain data source — Connect your OpenSearch cluster (self-managed or OpenSearch Cloud / Amazon OpenSearch Service), build metrics and dashboards, and embed them with the same governance and UX as the rest of your analytics.
• Use cases — Log analytics, search analytics, and application/event data in one place with your business metrics.
• No ETL required — Query OpenSearch directly from DataBrain; combine it with other sources on the same dashboard.
• Open source friendly — Stays on the Apache-2.0 OpenSearch stack.

Try DataBrain · OpenSearch connection guide · Contact us

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