The 2025 Masterclass: JdbcClient Multi-Value Binding

Introduction: The Evolution of Spring JDBC

For years, developers working with the Spring Framework have relied on JdbcTemplate and its more sophisticated sibling, NamedParameterJdbcTemplate, for direct SQL access. These tools have been the bedrock of data persistence, offering a solid abstraction over raw JDBC. However, as modern application development trends towards more fluent, readable, and less verbose APIs, the Spring team recognized an opportunity for improvement.

Enter JdbcClient, the new star player introduced in Spring Framework 6.1 and Spring Boot 3.2. It provides a modern, fluent API that simplifies database operations without sacrificing power. One of the most significant pain points it addresses is the clunky handling of dynamic SQL IN clauses. This masterclass will dive deep into JdbcClient's elegant solution: multi-value binding.

What is Spring's JdbcClient?

At its core, JdbcClient is a non-blocking, fluent client for JDBC operations. It's designed to be a single, streamlined entry point for your database interactions. Think of it as a wrapper that combines the best features of JdbcTemplate and NamedParameterJdbcTemplate into a more intuitive and chainable interface.

To get started, you simply autowire it into your service or repository:

@Repository
public class ProductRepository {

    private final JdbcClient jdbcClient;

    @Autowired
    public ProductRepository(JdbcClient jdbcClient) {
        this.jdbcClient = jdbcClient;
    }

    // ... repository methods
}

With this simple setup, you're ready to perform queries, updates, and more, with significantly less boilerplate code.

The Classic Challenge: Dynamic SQL IN Clauses

Anyone who has worked with SQL in Java has faced this issue: you need to select records where a column value is present in a dynamic list of values. For example, finding all products with a list of IDs.

With NamedParameterJdbcTemplate, the solution was functional but verbose. You had to pass a List or array as a parameter, and the template would expand it. Here's a typical example:

// The 'old' way with NamedParameterJdbcTemplate
List<Long> productIds = List.of(101L, 102L, 105L);
String sql = "SELECT id, name, price FROM products WHERE id IN (:ids)";

MapSqlParameterSource params = new MapSqlParameterSource();
params.addValue("ids", productIds);

List<Product> products = namedParameterJdbcTemplate.query(sql, params, new BeanPropertyRowMapper<>(Product.class));

While this works, it requires creating a MapSqlParameterSource and manually adding the parameter. It's not overly complex, but it adds a few extra lines and a layer of indirection that can clutter your data access code.

The Modern Solution: JdbcClient's Multi-Value Binding

JdbcClient completely revolutionizes how we handle IN clauses. It directly supports multi-value binding within its fluent API, making the code more concise and readable.

The Core Syntax Explained

The magic lies in the .param() method. When you provide a Collection (like a List or Set) as the value for a named parameter, JdbcClient automatically understands that it needs to expand this into a comma-separated list of bind markers for the prepared statement.

Let's rewrite the previous example using JdbcClient:

// The 'new' way with JdbcClient
List<Long> productIds = List.of(101L, 102L, 105L);
String sql = "SELECT id, name, price FROM products WHERE id IN (:ids)";

List<Product> products = jdbcClient.sql(sql)
        .param("ids", productIds) // Multi-value binding happens here!
        .query(Product.class)
        .list();

Look at how clean that is! The intent is immediately clear. We define the SQL, bind the list of IDs directly to the :ids placeholder, specify the result type, and execute. No intermediate parameter maps are needed. The fluent, chainable API guides you from SQL definition to result retrieval in a single, elegant statement.

A Practical, Complete Example

Let's see this in the context of a full repository method. Assume we have a Product record and a repository to fetch products.

// Product.java
public record Product(Long id, String name, double price) {}

// ProductRepository.java
import org.springframework.jdbc.core.simple.JdbcClient;
import org.springframework.stereotype.Repository;
import java.util.List;
import java.util.Set;

@Repository
public class ProductRepository {

    private final JdbcClient jdbcClient;

    public ProductRepository(JdbcClient jdbcClient) {
        this.jdbcClient = jdbcClient;
    }

    /**
     * Finds products by a dynamic set of status strings.
     * @param statuses A set of statuses like {"ACTIVE", "IN_STOCK"}
     * @return A list of matching products.
     */
    public List<Product> findProductsByStatuses(Set<String> statuses) {
        // Handle the edge case of an empty list to avoid SQL errors.
        if (statuses == null || statuses.isEmpty()) {
            return List.of();
        }

        String sql = "SELECT id, name, price, status FROM products WHERE status IN (:statuses)";

        return jdbcClient.sql(sql)
                .param("statuses", statuses) // Works with Sets, too!
                .query(Product.class)
                .list();
    }
}

This example demonstrates how effortlessly JdbcClient handles a Set of String values. It's important to handle the edge case of an empty collection, as most databases will throw an SQL syntax error for an empty IN () clause.

JdbcClient vs. NamedParameterJdbcTemplate: A Head-to-Head Comparison

Advanced Tips and Best Practices

While multi-value binding is straightforward, a few tips can help you use it most effectively.

Performance Considerations

Because JdbcClient uses NamedParameterJdbcTemplate under the hood, the performance characteristics are identical. The SQL statement is parsed, the collection is expanded into question mark placeholders (?), and a PreparedStatement is created. There is no performance penalty for using the more convenient JdbcClient API. The primary benefit is improved developer experience and code maintainability.

Combining Multi-Value and Single-Value Parameters

Real-world queries are often more complex. JdbcClient makes it trivial to mix and match single and multi-value parameters. You simply chain more .param() calls.

public List<Product> findActiveProductsInCategories(List<String> categories, double minPrice) {
    if (categories == null || categories.isEmpty()) {
        return List.of();
    }

    String sql = """
        SELECT id, name, price, category 
        FROM products 
        WHERE category IN (:cats) AND price > :minPrice AND status = 'ACTIVE'
    """;

    return jdbcClient.sql(sql)
            .param("cats", categories)      // Multi-value parameter
            .param("minPrice", minPrice)      // Single-value parameter
            .query(Product.class)
            .list();
}

This example showcases the power and clarity of the fluent API. The query's parameters are listed sequentially, making the code self-documenting and easy to debug.

Conclusion: Why You Should Switch to JdbcClient Today

The introduction of JdbcClient marks a significant step forward for JDBC access in the Spring ecosystem. Its fluent API, combined with powerful features like first-class support for multi-value binding, removes legacy boilerplate and lets developers focus on writing clean, expressive, and maintainable data access code.

If you are starting a new project on Spring Boot 3.2+ or have the opportunity to refactor existing data access layers, embracing JdbcClient is a clear win. The simplified handling of dynamic IN clauses is just one of many reasons to make the switch and modernize your application's persistence layer for 2025 and beyond.