How to Install and Use DataEase: Open‑Source BI with Apache Doris and Docker

Previously a reader asked for a good BI (Business Intelligence) tool; DataEase is an open‑source data visualization platform built on SpringBoot, integrating Apache Doris and Kettle for fast, large‑scale queries.

Introduction

DataEase claims to be

usable by anyone

, has over 4.1K stars on GitHub, and helps users quickly analyze data and gain business insights. It supports many data source connections, drag‑and‑drop chart creation, and sharing.

Architecture

As a data visualization tool, DataEase uses popular big‑data technologies Apache Doris and Kettle, making it a good project to learn these technologies.

System Architecture

The technology stack includes:

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 – UI component library

Installation

DataEase provides an installation package; run the install.sh script after downloading the v1.5.2 release (https://github.com/dataease/dataease/releases). Ensure MySQL is already installed.

Download the v1.5.2 package and upload it to a Linux server.

Extract it:

<code>tar -zxvf dataease-v1.5.2-online.tar.gz</code>

Edit

install.conf

to set the service port (

DE_PORT

) and MySQL configuration.

Modify

dataease/docker-compose.yml

to adjust container names and network settings.

Modify

dataease/docker-compose-kettle-doris.yml

to change the network subnet.

Modify

dataease/docker-compose-mysql.yml

if needed.

Open firewall port 8010 if applicable:

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

Run the installer:

<code>./install.sh</code>

After installation, update MySQL connection in

/opt/dataease/conf/dataease.properties

to use the new container name.

Restart the DataEase container:

<code>docker restart dataease</code>

Check logs with

docker logs -f dataease

until the database import finishes.

Control the service via systemd:

<code># view status
systemctl status dataease
# start
systemctl start dataease
# stop
systemctl stop dataease</code>

Usage

DataEase enables easy data visualization; the following examples use Excel and MySQL data.

Basic Concepts

Data source – connection information for databases such as MySQL, Elasticsearch, MongoDB.

Dataset – a collection of data from Excel, tables, or custom SQL queries.

View – the smallest visual unit (line chart, bar chart, pie chart, etc.).

Dashboard – a screen composed of multiple views.

Template – pre‑built styles for quick dashboard creation.

Excel Data Analysis

Log in with

admin:dataease

at

http://<span>$LOCAL_IP</span>:8010

.

Create a dataset by uploading the sample Excel file (sales_dashboard.xlsx).

Build a view (e.g., a pie chart) by selecting dimensions and metrics, then save.

Combine multiple views into a dashboard via drag‑and‑drop.

Database Data Analysis

Create a data source for MySQL.

Create a dataset from the MySQL source or via custom SQL.

Build views using the dataset; enable field‑level linkage for interactive filtering.

Use drill‑down to explore hierarchical data (e.g., province → city).

Conclusion

DataEase is a powerful, code‑free BI tool that supports visual analysis from various data sources, leveraging modern big‑data technologies like Apache Doris and Kettle. It is suitable for users who want quick dashboards without writing code.