DEV Community: Nikita Koksharov

Feature Comparison: Valkey and Redis vs. Hazelcast

Nikita Koksharov — Wed, 04 Jun 2025 11:57:54 +0000

In-memory data stores are a critical building block for developers of high-performance, distributed applications. Data stores go past the limitations of traditional relational databases by moving data in and out of system memory instead of slower, disk-based reads and writes. Developers use data stores as caches, message queues, and more for their raw speed and scalability.

The most popular choices for Java developers are Valkey, the open-source offshoot of the long-standing Redis project, Redis or Hazelcast. Although Valkey and Redis don’t support Java natively, the Redisson client addresses this issue and adds new features via familiar classes and methods. Hazelcast is an in-memory data grid written in Java that’s often used in distributed applications.

This comparison will look at Valkey/Redis (plus Redisson) and Hazelcast to help you understand their features, capabilities, performance, and more. In the end, you will have the knowledge to pick the best in-memory data store for you or your Java development team.

API Architecture

The first feature we'll compare is the API architecture offered by Redis/Valkey plus Redisson versus that of Hazelcast. The design and flexibility of an API are critical for building responsive, scalable applications. Redisson offers a comprehensive suite of API styles to support varying application architectures.

For example, it has a fully asynchronous API for all operations. This allows developers to write non-blocking code, freeing up threads to handle other requests while waiting for data to come in or out. Hazelcast offers asynchronous support for some of its methods, but it lacks Redisson's support for reactive programming paradigms like Reactive Streams or RxJava.

Feature	Valkey or Redis + Redisson	Hazelcast
Asynchronous interface	✔	partial support
Reactive stream interface	✔	❌
RxJava3 interface	✔	❌

Collections

Redisson leverages the rich data structures of Valkey/Redis to deliver distributed collections that mirror standard Java collection interfaces. This includes RMap object, which implements java.util.concurrent.ConcurrentMap and java.util.Map to give developers a familiar API with added features. Hazelcast offers a handful of distributed collections, although not as many as Redisson.

Feature	Valkey or Redis + Redisson	Hazelcast
Map	✔	✔
Multimap	✔	✔
JSON Store	✔	❌
Set	✔	✔
List	✔	✔
SortedSet	✔	❌
ScoredSortedSet	✔	❌
TimeSeries	✔	❌

Queues

Distributed queues are fundamental building blocks of asynchronous communication and other traits of modern applications. Redisson provides a comprehensive suite of queue implementations. This includes Reliable Queue, which ensures a message will eventually be processed even if the consumer crashes. Hazelcast also offers a few different queues, built around its stream processing engine.

Feature	Valkey or Redis + Redisson	Hazelcast
Reliable Queue	✔	❌
Reliable Fanout	✔	❌
Queue	✔	✔
Deque	✔	❌
PriorityQueue	✔	✔
PriorityDeque	✔	❌
TransferQueue	✔	❌
RingBuffer	✔	✔
Stream	✔	❌

Objects

Beyond standard collections and queues, modern distributed applications require tools and data structures to manage individual objects or publish/subscribe (pub/sub) messaging. Redisson offers a long list of specialized distributed objects, while Hazelcast only has some equivalents.

Feature	Valkey or Redis + Redisson	Hazelcast
Object holder	✔	✔
JSON holder	✔	❌
Topic (Pub/Sub)	✔	✔
Reliable Topic (Pub/Sub)	✔	✔
Geospatial	✔	❌
BitSet	✔	❌
BloomFilter	✔	❌
BinaryStream	✔	❌
HyperLogLog	✔	✔
RateLimiter	✔	❌

Counters

From generating unique IDs and tracking statistics to managing resource counts and coordinating distributed operations, counters are an essential tool for today's enterprise developers. Redisson meets this need by providing distributed versions of common Java atomic number classes and specialized counters. In comparison, Hazelcast only covers the basic use cases with tools for ID generation and atomic long operations.

Feature	Valkey or Redis + Redisson	Hazelcast
Id Generator	✔	✔
AtomicLong	✔	✔
AtomicDouble	✔	❌
LongAdder	✔	❌
DoubleAdder	✔	❌

Locks and Synchronizers

Coordinating access to shared resources and aligning operations across multiple nodes requires developers to employ various locks and synchronizers. Redisson offers multiple innovative solutions, such as FairLock, which guarantees that threads attempting to acquire a lock are serviced in the order they requested it. Meanwhile, Hazelcast has tools similar to some of Redisson's offerings, but not all of them.

Feature	Valkey or Redis + Redisson	Hazelcast
Lock	✔	✔
Semaphore	✔	✔
CountDownLatch	✔	✔
FairLock	✔	❌
Fenced Lock	✔	✔
Spin Lock	✔	❌
MultiLock	✔	❌
ReadWriteLock	✔	❌

Advanced Caching

Caching used to only be about storing frequently-used data in memory for faster access. Today's more complex applications utilize much more sophisticated caching strategies to maximize performance, reduce latency, and ensure data consistency. Both Valkey/Redis with Redisson and Hazelcast offer modern caching options.

Feature	Valkey or Redis + Redisson	Hazelcast
Near Cache	✔	✔
Read-through strategy	✔	✔
Write-through strategy	✔	✔
Write-behind strategy	✔	✔

Cache API Implementations

Developers today expect standardized caching APIs and direct integration with popular frameworks, so they don't have to write custom code to access critical features. Both Redisson PRO and Hazelcast support a wide range of cache API implementations, although only Redisson can work with Quarkus's caching annotations and infrastructure.

Feature	Valkey or Redis + Redisson	Hazelcast
JCache API	✔	✔
JCache API with near cache	✔	✔
Spring Cache	✔	✔
Spring Cache with near cache	✔	✔
Hibernate Cache	✔	✔
Hibernate Cache with near cache	✔	✔
MyBatis Cache	✔	✔
MyBatis Cache with near cache	✔	✔
Quarkus Cache	✔	❌
Quarkus Cache with near cache	✔	❌
Micronaut Cache	✔	✔
Micronaut Cache with near cache	✔	✔

Transactions

Both Redisson and Hazelcast support transactional operations, which are critical for maintaining data consistency across multiple operations and data sources.

Feature	Valkey or Redis + Redisson	Hazelcast
Transactions API	✔	✔
XA Transactions	✔	✔

Session Management

In modern web applications designed for high availability, developers must find ways to manage HTTP sessions effectively. Storing sessions in a distributed, fault-tolerant manner ensures that user session data is not lost if a server instance fails and that users can be seamlessly routed to an available node. Both Redisson and Hazelcast support popular session management frameworks.

Feature	Valkey or Redis + Redisson	Hazelcast
Micronaut Session	✔	✔
Tomcat Session Manager	✔	✔
Spring Session	✔	✔

Services

Redisson and Hazelcast both provide Java developers with distributed services to simplify computations, schedule tasks, and interact with data in sophisticated ways. However, only Redisson supports remote procedure calls (RPCs) with its RemoteService and live Java objects via the LiveObjectService.

Feature	Valkey or Redis + Redisson	Hazelcast
ExecutorService	✔	✔
MapReduce	✔	✔
SchedulerService	✔	✔
Search capabilities	✔	✔
RemoteService	✔	❌
LiveObjectService	✔	❌

Security

Both Redisson PRO and Hazelcast support standard security mechanisms such as authentication, password encryption, and SSL.

Feature	Valkey or Redis + Redisson	Hazelcast
Authentication	✔	✔
Authorization	✔	✔
SSL support	✔	✔
Passwords encryption	✔	✔

Data Serialization

The ability to serialize data is important for distributed applications, as it increases efficiency, reduces network bandwidth, and requires less storage. Redisson offers an extensive range of built-in codecs, giving developers more flexibility in the formats they can work with. Hazelcast supports the JSON codec but relies on its own serialization methods.

Feature	Valkey or Redis + Redisson	Hazelcast
JSON codec	✔	✔
JDK Serialization	✔	❌
Avro codec	✔	❌
Apache Fury codec	✔	❌
Smile codec	✔	❌
CBOR codec	✔	❌
MsgPack codec	✔	❌
Kryo codec	✔	❌
Protobuf codec	✔	❌
LZ4 compression codec	✔	❌
ZStandard compression codec	✔	❌
Snappy compression codec	✔	❌

Stability and Ease of Use

Developers must have stable tools that are easy to use. The list of features, no matter how long or varied, is not important if the software is not dependable or doesn't fit into a developer's tech stack. While both Redisson and Hazelcast are intuitive for Java developers, Redisson offers more flexible deployment options.

With support for all popular managed services, like AWS Elasticache and Azure Cache, Redisson is ready for nearly any development environment. Hazelcast users, on the other hand, are limited to the Hazelcast Cloud. And when it comes to handling large amounts of memory, Hazelcast's open source version has some limitations, while Redisson has no issues.

Feature	Valkey or Redis + Redisson	Hazelcast
Fully-managed services support (AWS Elasticache, Azure Cache...)	✔	Hazelcast Cloud
Large memory amount handling	✔	Open-source version has limitations

Valkey/Redis vs. Hazelcast: Who is the Winner?

Both Redisson, backed by Valkey or Redis, and Hazelcast offer Java developers familiar tools for building distributed applications around high-performance data stores. But, as this feature comparison shows, Redisson provides more features and flexibility. For most Java developers, the combination of Redisson and Valkey/Redis will be the clear winner.

Feature Comparison: Reliable Queue vs. Valkey and Redis Stream

Nikita Koksharov — Thu, 15 May 2025 08:16:43 +0000

Valkey and Redis streams are data structures that act like append-only logs with some added features. Redisson PRO, the Valkey and Redis client for Java developers, improves on this concept with its Reliable Queue feature.

While both Redisson PRO Reliable Queue and Valkey/Redis streams are advanced data structures for distributed messaging, each has distinct features and semantics for different use cases. Here is a detailed comparison of Reliable Queue vs. Valkey/Redis streams to help you decide which is best for your enterprise-grade applications.

Features Offered by Redisson PRO Reliable Queue

Message Acknowledgment

Reliable Queue provides either manual or automatic message acknowledgment. Valkey/Redis streams support acknowledgment per consumer group, and unacknowledged messages are tracked as "pending."

Negative Message Acknowledgment

Negative acknowledgment ("nack") allows consumers to explicitly reject a message. Nack provides fine-grained error handling and faster recovery from known failure scenarios. Reliable Queue implements negative message acknowledgment with a status of "failure" or "reject." Meanwhile, Valkey and Redis streams do not offer negative message acknowledgments.

Use cases : Skipping known-bad messages without blocking the queue, automatically escalating persistent failures to support teams, and implementing adaptive retry strategies based on error types

Visibility Timeout

After a message is sent to a consumer, a visibility timeout makes it temporarily invisible to others for a set time. If the consumer doesn't confirm receipt within this period, the message reappears and can be processed again. This mechanism avoids processing the same message multiple times and improves reliability, particularly in distributed environments where consumers might fail or disconnect.

Reliable Queue has a visibility timeout feature that is configurable per message or poll. Valkey and Redis streams have no comparable feature.

Use cases : Long-running tasks like image or video processing, preventing duplicate work in microservice architectures, and reliable work distribution in environments with unstable consumers.

Dead-Letter Queue (DLQ)

A DLQ acts as a temporary holding place for messages that cannot be successfully processed, where they can be inspected and analyzed. DLQs facilitate simpler debugging, monitoring, and manual handling of messages without risking data loss or perpetual retries of failed messages.

Reliable Queue has a built-in DLQ, configurable per queue. This is another feature that is not supported by Valkey and Redis streams.

Use cases : Handling malformed or "poison" messages in event-driven systems, ensuring critical business workflows don't become blocked due to unprocessable events, and meeting regulatory or audit requirements to retain failed messages for inspection.

Message Priorities

Priority queues allow specific messages to be processed before others based on their importance or urgency. Messages in Valkey/Redis streams have no concept of message priority. However, Reliable Queue supports message priority levels from 0 to 9. Message priorities are critical for systems where some tasks are more important than others

Use cases : Real-time alert systems in security or health monitoring applications, as well as customer support systems where high-priority tickets must be addressed first, and expedited financial transaction processing for VIP clients.

Delayed and Scheduled Messages

Delayed or scheduled messages allow tasks to be processed at a later date. This feature supports workflows that require deferred execution or scheduled jobs. Reliable Queue allows you to delay or schedule on a per-message basis. Valkey/Redis streams don't support delayed or scheduled messages.

Use cases : Scheduled notifications or reminders, time-based order processing such as in flash sales or auctions, and applications with retry mechanisms with backoff for transient failures.

Deduplication

Message deduplication is critical in distributed systems. It prevents the same message from being processed multiple times due to network issues or producer errors, events that can result in duplicate messages. Reliable Queue ensures message deduplication by examining the ID or payload hash, with a configurable time window. No deduplication features are available in Valkey or Redis streams.

Use cases : Financial systems with no tolerance for duplicate transactions, ensuring unique event processing with IoT telemetry data, and preventing data inflation in log aggregation operations.

Bulk Operations

Reliable Queue allows for numerous bulk operations, including batch add, poll, ack, and others. Valkey/Redis streams support batch read operations, but batch ack must be managed by the client.

Queue Size Limits

You can't set a queue size limit in Valkey or Redis streams. However, Reliable Queue supports configurable queue size limits.

Message Expiration

Valkey/Redis streams don't support message expiration, but you can set a per-message TTL (time to live) with Reliable Queue.

Synchronous Replication

Reliable Queue supports synchronous replication with multiple configurable sync modes for durability. Synchronous replication is not available in Valkey and Redis streams.

Consumer Model

While Valkey/Redis streams support consumer groups, with each message delivered to one consumer within a group, Reliable Queue allows for competing consumers via queue semantics.

Reliable Queue vs. Valkey/Redis Streams: The Final Verdict

Valkey/Redis streams provide a basic log of events and messages with consumer groups for parallel consumption. Messages must be explicitly acknowledged, and those that are unacknowledged remain in pending status. There is no native DLQ or message visibility timeout, which leaves it up to consumers to monitor and claim pending messages if needed.

Redisson PRO Reliable Queue, on the other hand, offers a strict FIFO queue with message visibility timeouts, delivery limits, and automatic DLQ handling. Reliable Queue is designed for scenarios where message loss is unacceptable and developers require processing guarantees. In addition, negative acknowledgments in Reliable Queue allow for fine-grained error handling with options to retry or reject to the DLQ.

Reliable Queue provides advanced features ideal for complex job processing pipelines, such as message priorities, per-message delays, deduplication (by ID/hash), size limits, and message TTLs. Valkey/Redis streams lack built-in support for these features, so they must be implemented at the application level.

In the final verdict, Reliable Queue is the more durable and feature-rich option. Standard Valkey/Redis streams will suffice for smaller applications, but Reliable Queue provides the enterprise-grade reliability that businesses depend on. To learn more, visit the Redisson PRO website today.