dataease/dataease

Overview

DataEase is an open-source business intelligence tool for analyzing data and presenting business trends through charts and dashboards. Users connect relational databases, analytical databases, data warehouses, files, or APIs, then assemble visualizations with drag-and-drop actions and share results with others. It targets analysts and teams that need self-service BI without building a visualization stack from scratch.

Supported sources span OLTP databases such as MySQL, PostgreSQL, Oracle, and SQL Server; OLAP systems such as ClickHouse, Apache Doris, and StarRocks; data files such as Excel and CSV; and API data sources README source. The frontend uses Vue.js and AntV charts, while the backend runs on Spring Boot and uses MySQL for storage README source.

Quick Start

The documented Linux path requires a server with at least 2 CPU cores and 4 GB of memory. Download the offline installer from the Feizhiyun open-source community, then unpack and install it:

tar zxvf dataease-offline-installer-v3.0.0.tar.gz
cd dataease-offline-installer-v3.0.0
bash install.sh

After installation, the documented default credentials are admin / DataEase@123456 installer steps. As an alternative, DataEase can be deployed from the 1Panel app store. For further setup and usage, see the online documentation and community forum.

Usage Constraints

The quick-start path assumes a Linux server and an offline installer; Windows or macOS desktop installation is not described in the provided material. The default credentials should be changed after the first login, although the README does not spell out that procedure. DataEase V3 is distributed under the FIT2CLOUD Open Source License, which is based on GPLv3 with additional conditions: derivative works must keep the DataEase logo and copyright information unchanged and must comply with GPLv3 obligations. Commercial licensing is available separately license terms.

HotRepo's take

On the Java daily chart for 2026-11-12, DataEase recorded 24,690 stars and 4,262 forks, gained 3 stars, and reached a best position of 12. This is a single daily observation, so it shows continued visibility in the Java ecosystem rather than a growth trend. The project's practical draw is its combination of broad source connectivity, drag-and-drop dashboarding, and a self-hosted Linux deployment; teams that need a Tableau-style workflow and can accept the license restrictions are the clearest fit.