DataEase: Open‑Source Data Visualization Tool Based on SpringBoot, Apache Doris, and Kettle – Installation and Usage Guide

DataEase is an open‑source data‑visualization and analysis platform that aims to be “everyone‑usable”, built on SpringBoot and integrating Apache Doris and Kettle for large‑scale, second‑level queries.

Overview

DataEase supports rich data‑source connections, drag‑and‑drop chart creation, and sharing capabilities, with over 4.1K stars on GitHub.

Architecture

The technology stack includes:

Technology

Description

SpringBoot

Backend framework

MySQL

Data storage

Apache Doris

Modern MPP analytical database with sub‑second query response

Kettle

Open‑source ETL tool written in Java

Docker

Containerized deployment

Vue

Frontend framework

Element

Frontend UI library

These components work together to provide fast data ingestion, processing, and visualization.

Installation

Download the v1.5.2 package from the GitHub releases page, extract it, and edit install.conf to set the service port ( DE_PORT ) and MySQL parameters.

tar -zxvf dataease-v1.5.2-online.tar.gz

After extraction, the dataease directory contains a Docker‑Compose script. Modify docker-compose.yml to adjust the MySQL container name and network settings, then run the installation script:

./install.sh

The script pulls Docker images for DataEase, Doris, Kettle, and MySQL, creates the containers, and starts the services. Open port 8010 in the firewall if needed:

firewall-cmd --zone=public --add-port=8010/tcp --permanent
firewall-cmd --reload

After installation, edit /opt/dataease/conf/dataease.properties to point to the correct MySQL host and restart the DataEase container:

docker restart dataease

Check the service status with:

systemctl status dataease

Usage

Log in with the default credentials admin:dataease at http:// $LOCAL_IP :8010 . Create a data source (MySQL, Elasticsearch, MongoDB, etc.), then create a dataset by uploading an Excel file or connecting to a database. Build views (e.g., pie charts) by selecting dimensions and metrics, and assemble them into a dashboard via drag‑and‑drop.

DataEase also supports view linking (drill‑through) and custom SQL queries for advanced analysis.

Conclusion

DataEase provides a code‑free way to perform data visualization and analysis, supporting multiple data sources and leveraging modern big‑data technologies such as Apache Doris and Kettle, making it a valuable tool for both developers and business users.