Spring Data JPA Batch DML

Comparison of 5 batch insert strategies using Spring Data JPA and PostgreSQL.

Strategies

Strategy	Description
Hibernate Batch	EntityManager.persist() + flush with hibernate.jdbc.batch_size and reWriteBatchedInserts
JDBC Batch	JdbcTemplate.batchUpdate() with native SQL
UNNEST	INSERT ... SELECT FROM UNNEST(...) — single SQL statement using PostgreSQL arrays
COPY	COPY ... FROM STDIN — PostgreSQL binary protocol via CopyManager
Multi-row VALUES	INSERT INTO ... VALUES (...), (...), ... — single statement with all rows as parameter placeholders

Project Structure

spring-data-jpa-batch-dml/
├── batch-core/          # Models, repositories, services, utilities (JAR)
├── web/                 # Spring Boot app, controllers, records (bootJar)
├── benchmark/           # JMH benchmarks
└── docker-compose.yml   # PostgreSQL 17

Modules

• batch-core — shared business logic (JPA entities, repositories, 5 CustomerService implementations)
• web — Spring Boot application with REST API (/customers, /stores), Spring Boot Admin, Springdoc
• benchmark — JMH benchmarks comparing the 5 batch insert strategies

Prerequisites

• Java 17+
• Docker (for PostgreSQL)

Getting Started

# Start PostgreSQL
docker compose up -d

# Build
./gradlew clean build -x test

# Run the application
./gradlew :web:bootRun

The application starts on port 8081.

API

# Batch insert (modes: jdbc, hibernate, unnest, copy, multirow)
curl -X POST "http://localhost:8081/customers/save-all?number=1000&mode=multirow"

# Get all customers
curl http://localhost:8081/customers/get-all

# Get all with store and orders (eager fetch)
curl http://localhost:8081/customers/get-all-with-store-orders

# Delete all
curl -X DELETE http://localhost:8081/customers/delete-all

Tests

# Unit tests (H2)
./gradlew :web:test

# Integration tests (requires PostgreSQL)
./gradlew :batch-core:integrationTest

JMH Benchmarks

# Run benchmarks (requires PostgreSQL)
./gradlew :benchmark:jmh

Results are written to benchmark/build/reports/jmh/results.json.

Results (1,000 customers + 1,000 orders per batch)

Environment: JDK 17.0.18 (OpenJDK), PostgreSQL 17 (Docker), batch_size=100, reWriteBatchedInserts=true

JMH config: fork=1, warmup=1x3s, measurement=3x5s, mode=AverageTime

Strategy	Avg (ms/op)	Error (ms)
UNNEST	17.47	± 21.90
Multi-row VALUES	23.48	± 59.64
JDBC Batch	23.68	± 82.60
COPY	42.39	± 200.45
Hibernate Batch	182.82	± 434.61

UNNEST is the fastest for 1,000 rows, followed closely by multi-row VALUES and JDBC Batch. Hibernate Batch is significantly slower due to the persistence context overhead (dirty checking, cascade).

Tech Stack

• Spring Boot 3.2.2
• Spring Data JPA / Hibernate 6.4
• PostgreSQL 17
• Lombok
• JMH 1.37
• Gradle 8.5 (multi-module)