appbaseio/dejavu

A Web UI for Elasticsearch and OpenSearch: Import, browse and edit data with rich filters and query views, create reference search UIs.

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Summary Information

Updated 27 minutes ago
Added to GitGenius on September 7th, 2026
Created on February 3rd, 2016
Open Issues & Pull Requests: 69 (+0)
GitHub issues: Enabled
Number of forks: 512
Total Stargazers: 8,467 (+0)
Total Subscribers: 122 (+0)

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Detailed Description

Dejavu is a web UI for browsing, editing, and managing data in Elasticsearch and OpenSearch clusters.

The tool addresses the need for a user-friendly interface to interact with Elasticsearch and OpenSearch without relying on command-line tools or complex query syntax. It provides visual filtering, real-time updates, and infinite scroll capabilities with no page reloads. The interface is built entirely on the client side, allowing it to run as a hosted application or as a Docker container. Users can connect to indices in their cluster, and the tool caches connection details locally for quick access on subsequent visits.

Developers managing Elasticsearch or OpenSearch clusters benefit most from Dejavu when they need to browse, filter, and edit data through a graphical interface. It suits teams that want to import data from JSON or CSV files without writing custom scripts, as well as those building and testing search interfaces before deploying them to production. The tool's ability to export filtered views as JSON or CSV, perform bulk updates via query DSL, and support custom authentication headers makes it valuable for workflows involving data validation and search relevancy testing. The search UI builder with CodeSandbox export capability helps developers prototype search interfaces quickly.

The project maintains active development with regular feature additions across major versions. The codebase shows consistent refinement of core functionality, with improvements to filtering capabilities, multi-index support, and the search UI builder. Development activity demonstrates responsiveness to user needs through incremental enhancements rather than sporadic updates.