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Redis session store with Java (Lettuce)

Implement a Redis-backed session store in Java with Lettuce

This guide shows you how to implement a Redis-backed session store in Java with Lettuce. It includes both asynchronous and reactive store APIs, plus a small local demo server built on Java's built-in HttpServer.

Overview

Session storage is a common Redis use case for web applications. Instead of keeping session state in local process memory, you store it in Redis and send the browser only an opaque session ID in a cookie.

That gives you:

In this example, each session is stored as a Redis hash with a key like session:{session_id}. The hash holds lightweight fields such as the username, page view count, timestamps, and the configured session TTL. The key also has an expiration so inactive sessions are removed automatically.

Why async and reactive

For Lettuce, we generally show asynchronous and reactive APIs rather than a synchronous API:

How it works

The flow looks like this:

  1. A user submits a login form
  2. The server generates a random session ID with SecureRandom
  3. The server stores session data in Redis under session:{id}
  4. The server sends a sid cookie containing only the session ID
  5. Later requests read the cookie, load the hash from Redis, and refresh the TTL
  6. Logging out deletes the Redis key and clears the cookie

Because the cookie only contains an opaque identifier, the browser never receives the actual session data. That stays in Redis.

The Lettuce session stores

The async and reactive session store classes wrap the basic session operations:

Async usage

import io.lettuce.core.RedisClient;
import io.lettuce.core.api.StatefulRedisConnection;
import java.util.Map;

RedisClient redisClient = RedisClient.create("redis://localhost:6379");
StatefulRedisConnection<String, String> connection = redisClient.connect();

AsyncSessionStore store = new AsyncSessionStore(connection.async(), "session:", 1800);

store.createSession(Map.of(
        "username", "andrew",
        "page_views", "0"
), null)
    .thenCompose(sessionId -> store.getSession(sessionId, true))
    .thenAccept(session -> {
        if (session != null) {
            System.out.println(session.get("username"));
        }
    })
    .join();

connection.close();
redisClient.shutdown();

Reactive usage

import io.lettuce.core.RedisClient;
import io.lettuce.core.api.StatefulRedisConnection;
import java.util.Map;

RedisClient redisClient = RedisClient.create("redis://localhost:6379");
StatefulRedisConnection<String, String> connection = redisClient.connect();

ReactiveSessionStore store = new ReactiveSessionStore(connection.reactive(), "session:", 1800);

store.createSession(Map.of(
        "username", "andrew",
        "page_views", "0"
), null)
    .flatMap(sessionId -> store.getSession(sessionId, true))
    .doOnNext(session -> System.out.println(session.get("username")))
    .block();

connection.close();
redisClient.shutdown();

Data model

Each session is stored in a Redis hash:

session:abc123...
  username = andrew
  page_views = 3
  session_ttl = 15
  created_at = 2026-04-08T12:34:56Z
  last_accessed_at = 2026-04-08T12:40:10Z

The implementation uses:

The store treats created_at, last_accessed_at, and session_ttl as reserved internal fields, so caller-provided session data cannot overwrite them.

Session store implementation

The createSession() method generates a random session ID, writes the initial hash fields, and sets the TTL:

public CompletableFuture<String> createSession(Map<String, String> data, Integer ttl) {
    String sessionId = createSessionId();
    String key = sessionKey(sessionId);
    String now = timestamp();
    int sessionTtl = normalizeTtl(ttl);

    Map<String, String> payload = sessionPayload(data, now, sessionTtl);

    return commands.hset(key, payload)
            .toCompletableFuture()
            .thenCompose(ignore -> commands.expire(key, sessionTtl).toCompletableFuture())
            .thenApply(ignore -> sessionId);
}

When the application reads a session, it refreshes the configured TTL so active users stay logged in:

public CompletableFuture<Map<String, String>> getSession(String sessionId, boolean refreshTtl) {
    String key = sessionKey(sessionId);

    return commands.hgetall(key).toCompletableFuture().thenCompose(session -> {
        if (!isValidSession(session)) {
            return CompletableFuture.completedFuture(null);
        }
        if (!refreshTtl) {
            return CompletableFuture.completedFuture(session);
        }

        int sessionTtl = normalizeTtl(Integer.parseInt(session.get("session_ttl")));
        return commands.hset(key, "last_accessed_at", timestamp()).toCompletableFuture()
                .thenCompose(ignore -> commands.expire(key, sessionTtl).toCompletableFuture())
                .thenCompose(ignore -> commands.hgetall(key).toCompletableFuture())
                .thenApply(refreshed -> isValidSession(refreshed) ? refreshed : null);
    });
}

This is a simple and effective pattern for many apps. For more complex requirements, you might add separate metadata keys, rotate session IDs after login, or store less frequently accessed data elsewhere.

Installation

Add Lettuce to your project:

Running the demo

A local demo server is included to show the session store in action (source):

javac -cp lettuce-core-6.7.1.RELEASE.jar AsyncSessionStore.java DemoServer.java
java -cp .:lettuce-core-6.7.1.RELEASE.jar DemoServer

The demo uses the async Lettuce API and exposes a small interactive page where you can:

The demo assumes Redis is running on localhost:6379, but you can override that with --redis-host and --redis-port. After starting the server, visit http://localhost:8080.

Cookie handling

The browser cookie should contain only the session ID:

exchange.getResponseHeaders().add(
        "Set-Cookie",
        "sid=" + sessionId + "; Path=/; HttpOnly; SameSite=Lax"
);

Avoid storing user profiles, roles, or other sensitive session data directly in cookies. Keep that information in Redis and let the cookie act only as a lookup token.

Production usage

This guide uses a deliberately small local demo so you can focus on the Redis session pattern. In production, you will usually want to harden the cookie, session lifecycle, and deployment details around it.

Secure the session cookie

Set cookie attributes that match your deployment and threat model:

Keep session data lightweight

Redis-backed sessions work best when each session stores small, frequently accessed values:

Handle expiration deliberately

Sliding expiration is convenient, but it also defines how long a hijacked cookie remains useful. For production apps, consider:

Use a framework integration where appropriate

This example keeps everything explicit so you can see the Redis session pattern clearly. In a real app, you will often wrap the same Redis operations behind middleware for Spring WebFlux, Vert.x, Micronaut, or another Java framework using non-blocking I/O.

Next steps

You now have Redis-backed session examples in Java using both Jedis and Lettuce. From here you can:

For more Redis data modeling patterns, see:

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