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description: A practitioner-level walkthrough of OpenSearch Dashboards covering its architecture, Discover for data exploration, the four query languages (DQL, Lucene, PPL,...
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# OpenSearch Dashboards: A Complete Guide to Visualization and Analytics

**[BigData Boutique blog](https://daily.dev/sources/bigdataboutique)** · 12 min read · 0 upvotes · 0 comments

## Summary

A practitioner-level walkthrough of OpenSearch Dashboards covering its architecture, Discover for data exploration, the four query languages (DQL, Lucene, PPL, SQL, plus underlying Query DSL), visualization tools (classic aggregation charts, VisBuilder, Vega/Vega-Lite), workspaces versus Security plugin multi-tenancy, alerting and anomaly detection plugins, the OpenSearch Assistant's LLM dependency and privacy implications, multi-data-source connectivity, and a detailed feature comparison against Kibana in 2026 including licensing, ML, and migration considerations.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://bigdataboutique.com/blog/opensearch-dashboards-guide>

## Questions this post answers

### What's the difference between OpenSearch Dashboards workspaces and the Security plugin's multi-tenancy?

Workspaces scope saved objects per team through lighter, UI-driven boundaries, while Security plugin multi-tenancy enforces hard RBAC boundaries backed by role mapping. Workspaces suit team-level organization within a tenant, whereas multi-tenancy suits strict access boundaries between groups that must not see each other's objects. The two compose, since workspaces sit inside the access model the Security plugin defines.

_Teams designing access boundaries in OpenSearch can compare these tradeoffs alongside other architecture reads on daily.dev._

### Which query language should I use in OpenSearch Dashboards for piped log analytics versus BI tool connectivity?

PPL (Piped Processing Language) suits ad-hoc log triage and aggregation with a Unix-pipe model similar to Splunk SPL, needing no visualization. SQL suits joins and connecting external BI tools like Tableau or Grafana via JDBC/ODBC drivers. DQL remains the default for everyday dashboard and Discover filtering, and Lucene covers regex, proximity, and boosting that DQL lacks.

_Engineers choosing between query languages for log analytics can keep comparisons like this handy on daily.dev._

### Do OpenSearch Dashboards and the OpenSearch cluster need to run the exact same version?

No, within the same major version an exact match isn't required — a 2.17 Dashboards instance works fine against a 2.13 cluster. The hard boundary is the major version. Minor releases ship roughly every six weeks with patch releases for CVEs in between, and staying close in version is still recommended as good practice even though not strictly enforced.

_Ops teams planning OpenSearch upgrades can track version compatibility notes like this on daily.dev._

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---

Tags: [#observability](https://daily.dev/tags/observability), [#data-visualization](https://daily.dev/tags/data-visualization), [#elk](https://daily.dev/tags/elk), [#opensearch](https://daily.dev/tags/opensearch)

[View this post on daily.dev](https://daily.dev/posts/opensearch-dashboards-a-complete-guide-to-visualization-and-analytics-ohmilgolk)

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