Making Hibernate Performance Visible
A specialized analysis and visualization tool for Spring Boot applications in enterprise environments. Detects typical performance issues, visualizes runtime behavior, and provides assessments through local AI.
Why Performance Analysis?
N+1 Queries
One of the most common causes of latency in Hibernate applications. Instead of a targeted join, individual queries are fired for each association – often hundreds per request, without being directly visible in the code.
Inefficient Associations
Eager loading fetches data that is never used. Lazy loading triggers unexpected queries in loops. The right fetch strategy depends on the use case – and is rarely obvious at first glance.
Hidden Query Patterns
Hibernate generates SQL behind the scenes. Which queries are actually executed, how often, and with what latency – in most projects, this remains invisible until a production incident.
Planned Features
N+1 Detection & Association Analysis
Detection of N+1 problems at entity and repository level. Visualization of affected associations and their actual runtime behavior.
Query Monitoring & Hotspot Dashboard
Overview of query counts, execution times, and notable endpoints. Hotspots are displayed with priority to identify the biggest levers.
Entity Relationship Graph
Interactive visualization of entity relations with marking of critical paths, circular dependencies, and problematic fetch configurations.
Fetch Strategy Audit
Systematic analysis of eager vs. lazy loading configurations in the context of actual access patterns. Recommendations based on measured data.
HQL / JPQL Analysis
Identification of inefficient queries, missing projections, and unnecessarily broad SELECTs. Checks for missing indexes on frequently filtered fields.
Local AI Assessment
A locally running language model explains detected issues in plain language, assesses severity levels, and suggests actions – without sending data externally.
Analysis Views
Conceptual representation of planned visualizations.
Local AI – Data Stays in Your Organization
Many organizations cannot or do not want to send code and runtime data to external services. The scanner therefore relies on a locally running language model that contextualizes and explains analysis results – entirely on your own infrastructure.
- No code or runtime data leaves the local environment
- Explanations and assessments in natural language
- Prioritization by severity and estimated impact
- Integrable into existing development workflows
N+1 detected — Address
147 individual queries per request
KI-Einordnung
Die Entity Customer → Address verwendet Lazy Loading. Da Address in einer Schleife über alle Kunden geladen wird, entstehen 147 einzelne SELECTs. Empfehlung: JOIN FETCH im Repository oder@EntityGraph.
Current Status
The tool is currently in active development. I am working on the domain-specific design, the technical implementation, and initial validations of the analysis approaches. The features described here are at various stages of maturity.
Interested or Have Feedback?
If you work on performance optimization with Spring Boot and are interested in a tool like this – or would like to give feedback on the concept – I would be happy to hear from you.
Get in Touch