An integrated practicing platform for database courses.

An integrated practicing platform enhancing the learning experiences in database related courses.

Learning compass

Hover or focus to highlight · Positions indicate each tool’s primary focus

Scroll horizontally to view the full compass →

Level of focusOperator → plan → pipeline

Interaction with query plans(read · visualize · modify · diagnose · chat)

Full pipelineSQL → Query plan → executionQuery planThe plan as a wholeOperator / estimateIndividual operators or row estimates

ReadExplain the planVisualizeSee the pipelineModifyReplace & exploreDiagnoseLocate errorsChatAsk in natural language

Reading the map

NEURON and LANTERN support understanding query execution plans through natural language descriptions.

DBinsight visualizes the SQL-to-plan process.

MOCHA and ARENA explore operator and plan choices.

RETRO examines cardinality estimation errors.

ChatQPT supports conversation with a relational query engine.

Find your bottleneck

Pick the cluster that matches what’s blocking you. Each branch leads to a tool for that question.

Understand

“I have a query plan, but I don’t understand it.”

Modify

“What happens if I change one operator in the plan?”

MOCHAoperator choices

Explore

“What other query plans could the optimizer choose?”

ARENAalternative plans

Diagnose

“Where do estimated and actual row counts differ?”

RETROcardinality errors

Find your

Bottleneck

Choose the branch that matches your question

A typical learning pathUnderstand first, then iterate

Or ask in natural language

ChatQPT · a novel system that enables chat-based interactions with a relational query engine (PostgreSQL).

NEURON

Learn query execution plans generated by RDBMS based on natural language descriptions.

Open tool ↗Watch tutorial

MOCHA

A Tool for Visualizing Impact of Operator Choices in Query Execution Plans for Database Education.

Open tool ↗Watch tutorial

LANTERN

Boredom-conscious natural language description generation of query execution plans.

Open tool ↗Watch tutorial

ARENA

Learn database optimization by comparing query execution plan and alternative plans.

Open tool ↗Watch tutorial

RETRO

A visual tool for understanding cardinality estimation errors for database education.

Open tool ↗Watch tutorial

ChatQPT

a novel system that enables chat-based interactions with a relational query engine (PostgreSQL).

Open tool ↗Watch tutorial Open preview tool ↗

DBEDU in use

23Universities

87Teachers

—Users across systems

—Institutions across systems

By system

NEURON

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MOCHA

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Via ChatQPT

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LANTERN

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ARENA

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RETRO

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ChatQPT

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About & resources

About

DBEDU is presented by Prof. Hui Li and his group at Xidian University, in collaboration with Prof. Sourav S Bhowmick at Nanyang Technological University.

Prof. Hui Li

Project lead

Prof. Hui Li

Xidian University

Leads DBEDU at Xidian University, developing practical tools with his group for learning query execution plans and database optimization.

Prof. Sourav S Bhowmick

Collaborator

Prof. Sourav S Bhowmick

Nanyang Technological University

Collaborates with the Xidian University team on DBEDU research, exploring how interactive query-processing tools can support database education.

Supported databases+

Compatibility varies across subsystems.

The team

Current team

Dr. Xiyue Gao, Zihao Ma (Ph.D student), Zhenning Shi (Ph.D student), Yani Zhang (Ph.D student), Binying Zhai (Master student), and several undergraduates.

Alumni

Weiguo Wang (Alibaba), Peng Chen (Huawei), Hu Wang (China CITIC Bank), Ying Rong (Huawei), Baochao Xu (NARI-Relays).

Publications

Research behind the tools, from 2019 to the present.

Liu et al.NEURON: Query Execution Plan Meets Natural Language Processing For Augmenting DB Education
In ACM SIGMOD, 2019.
Paper Video
Wang et al.Towards Enhancing Database Education: Natural Language Generation Meets Query Execution Plans
In ACM SIGMOD, 2021.
Paper Video
Chen et al.LANTERN: Boredom-conscious Natural Language Description Generation of Query Execution Plans for Database Education
In ACM SIGMOD, 2022.
Paper Video
Jess et al.MOCHA: A Tool for Visualizing Impact of Operator Choices in Query Execution Plans for Database Education
In VLDB, 2022.
Paper Video
Rong et al.DBinsight: A Tool for Interactively Understanding the Query Processing Pipeline in RDBMSs
In CIKM, 2022.
Paper Video
Sourav S Bhowmick and Hui Li.Towards Technology-Enabled Learning of Relational Query Processing
In IEEE Data Eng. Bull. 45(3), 2022.
Paper
Wang et al.ARENA: Alternative Relational Query Plan Exploration for Database Education
In ACM SIGMOD, 2023.
Paper Video
Hui Li.Technology-Enabled Database Education: Challenges and Opportunities
SIGMOD Record, 53(2). 2024.
Paper
Sourav S Bhowmick and Hui Li.Experience Report on Using LANTERN in Teaching Relational Query Processing
In ACM SIGCSE 2025.
Paper
Li et al.Towards Selecting the Informative Alternative Relational Query Plans for Database Education
Proc. ACM Manag. Data 4(3), SIGMOD, 2026. ★ Best of SIGMOD
Paper
Zhang et al.RETRO: A Visual Tool for Understanding Cardinality Estimation Errors For Database Education
In ACM SIGMOD Companion, 2026. ★ SIGMOD Best Demonstration
Paper Video
Li et al.ChatQPT: Towards Conversing with Relational Query Engines
Proc. VLDB Endow. 19(12): 4758–4761, 2026.
Paper Video