# Valkey vs Redis: How to Choose in 2026

In-memory databases have become essential components of modern application
stacks, providing lightning-fast data access and processing capabilities that
traditional disk-based databases simply cannot match.

Among these, [Redis](https://github.com/redis/redis) has been a dominant force
for over a decade. However, the emergence of
[Valkey](https://github.com/valkey-io/valkey) in 2024 has created an interesting
fork in the road of in-memory database technology.

<iframe width="100%" height="315" src="https://www.youtube.com/embed/b8yANadT0Y4?si=AovMjgXa9R_HCwlV" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
This article provides a detailed comparison between Redis and Valkey, examining
their origins, technical capabilities, performance differences, and practical
considerations for common use cases.

Whether you're considering a migration or evaluating options for a new project,
this guide will help you make an informed decision.

Let's get started!

[ad-logs]

## Understanding the historical context

Redis was created by [Salvatore Sanfilippo](https://antirez.com/) (known as
"antirez" in the developer community) and first released in 2009. It quickly
gained popularity for its speed, simplicity, and versatility. Over the years,
Redis established itself as one of the most beloved databases among developers,
consistently ranking high in developer surveys.

![redis.png](https://imagedelivery.net/xZXo0QFi-1_4Zimer-T0XQ/d7825cfc-3b16-4151-1105-febad2ed0900/md1x =1200x600)

It was initially developed under the BSD 3-clause license, making it fully
open-source and available for both personal and commercial use. Redis Inc.
(formerly Redis Labs) emerged as the commercial entity supporting Redis,
offering enterprise features and support on top of the open-source core.

In early 2024, Redis Inc.
[made a significant change to its licensing strategy](https://redis.io/blog/redis-adopts-dual-source-available-licensing/).
The company moved away from the open-source BSD 3-clause license to a
"source-available" model with the Redis Source Available License (RSALv2) and
Server Side Public License (SSPLv1). While the source code remained accessible,
these licenses imposed new restrictions on usage, particularly affecting cloud
providers and commercial users.

This licensing change prompted a response from the developer community and major
tech companies. In March 2024,
[Valkey was born as a fork of Redis 7.2.4](https://www.linuxfoundation.org/press/linux-foundation-launches-open-source-valkey-community),
maintaining the original BSD 3-clause license. The project was backed by The
Linux Foundation and supported by major tech companies including Amazon Web
Services (AWS), Google Cloud, Oracle, Ericsson, and Snap Inc.

The creation of Valkey represents one of the most significant open-source forks
in recent years. According to
[research by Percona](https://www.percona.com/about-percona/newsroom/press-releases/valkey-emerges-as-leading-open-source-alternative-to-redis-after-relicensing-row),
approximately 75% of surveyed Redis users considered migration due to the
licensing changes, with more than three-quarters of those considering Valkey as
an alternative.

The fork has gained substantial momentum, with third-party Redis ecosystem
companies like Redisson announcing support for both Redis and Valkey. This
suggests Valkey is being treated as a serious long-term alternative rather than
a temporary protest.

## Architectural foundations: From shared DNA to divergent paths

Valkey began as a direct fork of Redis 7.2.4, meaning the initial version of
Valkey was essentially identical to Redis at that point in time. Both systems
share the same fundamental architecture and approach to data storage and
manipulation:

- In-memory data storage with optional persistence.
- Support for various data structures (strings, lists, sets, hashes, etc.).
- Pub/sub messaging capabilities.
- Lua scripting support.
- Replication and clustering.

While starting from the same codebase, Valkey and Redis have begun to diverge
significantly. By September 2024, Valkey released
[version 8.0](https://valkey.io/blog/valkey-8-0-0-rc1/), introducing substantial
changes to the core architecture and setting a distinct development path.

As Kyle Davis, a Valkey maintainer, stated: "From this point forward, Redis and
Valkey are two different pieces of software." This divergence is most apparent
in areas like threading models, performance optimizations, and how each project
approaches modern hardware utilization.

## Performance comparison

### Threading models

One of the most significant technical differences between Redis and Valkey lies
in their threading architectures:

- **Redis**: Traditionally uses a single-threaded event loop model for most
  operations. While this approach simplifies code and avoids complex concurrency
  issues, it can limit throughput on multi-core systems.

- **Valkey**: Has implemented enhanced I/O multithreading that better utilizes
  modern multi-core processors. Valkey 8.0 introduced a redesigned threading
  model that allows for parallel I/O operations while maintaining data safety.

### Throughput benchmarks

Valkey's multithreaded approach has led to significant performance improvements.
According to reports from the Linux Foundation Member Summit, Valkey 8.0's
enhanced multithreading delivers:

- Approximately three times the throughput compared to earlier versions.
- Up to 1.19 million requests per second with the new I/O threading model.
- Better scalability under high concurrent load.

Dirk Hohndel, a Linux kernel developer and open source leader,
[reported](https://thenewstack.io/valkey-is-a-different-kind-of-fork/) "roughly
a threefold improvement in performance" when streaming large volumes of data
(approximately 60 million data points daily) after switching to Valkey 8.0.

### Memory efficiency

Memory usage is a critical consideration for in-memory databases. Valkey has
made strides in this area:

- Valkey 8.1 introduced up to 20% memory efficiency improvements.
- The project rebuilt its key-value store from scratch based on modern data
  structures similar to Google's "Swiss Tables".
- Hohndel reported about a "20% reduction in the size of separate cache tables,"
  translating to significant cost savings when dealing with terabyte-scale
  datasets.

Redis also offers memory optimization features like memory eviction policies but
has not announced comparable efficiency gains in recent releases.

### Scalability capabilities

Both systems support clustering for horizontal scaling, but with some
differences:

- Redis Cluster provides sharding and high availability but requires careful
  management.
- Valkey has improved the internal algorithms for cluster mode, enhancing
  reliability and reducing failover times.
- Valkey's automatic cluster failover capabilities simplify management in
  distributed environments.

## Feature comparison

### Data structures

Both Redis and Valkey support a rich set of data structures, including:

- Strings,
- Lists,
- Sets,
- Sorted sets,
- Hashes,
- Bitmaps.
- HyperLogLogs,
- Streams,
- Geospatial indexes.

However, Redis offers additional features not currently available in Valkey:

- Native JSON support.
- Time Series data structure.
- Vector database capabilities for AI applications.
- Probabilistic data structures for efficient approximations.
- More extensive search and query capabilities through Redis Query Engine.

### Replication and clustering

Both systems support master-replica replication for data redundancy and read
scaling:

- Redis provides master-slave replication with Redis Cluster support.
- Valkey has implemented dual-channel replication, potentially offering improved
  reliability.

For clustering, both support distributed data storage across multiple nodes:

- Redis Cluster can scale to hundreds of nodes.
- Valkey clusters can scale up to 1000 nodes and have improved internal
  algorithms for cluster management.

### Unique features

**Redis unique features:**

- JSON: Native APIs for JSON document operations.
- Time Series: Specialized storage and querying for time-series data.
- Vector search: Support for AI and retrieval-augmented generation workflows.
- Redis Data Integration: Automatic synchronization with systems of record.
- Redis Insight: Analysis tools with AI-powered Redis Copilot.
- ODBC integration: Connectivity with BI tools and visualization frameworks.

**Valkey unique features:**

- Enhanced I/O multithreading for better multi-core utilization.
- Experimental Remote Direct Memory Access (RDMA) support.
- Per-slot metrics for detailed monitoring.
- Improved dictionary structure for memory optimization.
- Rust integration for memory safety in core components.

### Advanced session management

Redis 7.4 introduced hash field expiration, enabling advanced session management
capabilities. This feature allows developers to:

- Use Redis as a searchable session store.
- Implement multi-value indexing.
- Index at arbitrary depths.

This capability is not yet matched in Valkey, though the project continues to
evolve rapidly.

## Licensing and support

The licensing difference represents the initial and perhaps most fundamental
distinction between the two projects.

Redis now operates under the Redis Source Available License (RSALv2) and Server
Side Public License (SSPLv1), which allow access to source code but aren't fully
open-source by traditional definitions. Valkey, meanwhile, uses the BSD 3-clause
license, a permissive open-source license recognized by the Open Source
Initiative.

Support options differ significantly as well. Redis Inc. provides commercial
support through various subscription plans for different user segments, while
Valkey currently relies primarily on community support, though cloud providers
like AWS may offer managed Valkey services.

Documentation reflects the maturity difference between the projects. Redis has
extensive documentation built over many years, with comprehensive guides,
examples, and reference materials. Valkey's documentation is still developing,
though it benefits from similarity to Redis in many areas.

Regarding ecosystem compatibility, Redis has developed a robust ecosystem of
clients, tools, and extensions. Most Redis clients can work with Valkey due to
protocol compatibility, but feature support varies.

Redis-specific features like JSON or Vector Search require specialized clients
that may not work with Valkey. Some ecosystem tools are adapting to support both
platforms, as seen with
[Redisson announcing dual support](https://redisson.org/), suggesting Valkey is
being treated as a serious long-term alternative.

## Use cases and implementation scenarios

Redis remains particularly well-suited for:

- Organizations requiring enterprise-grade support and SLAs.
- Applications leveraging Redis-specific features like JSON, Time Series, or
  vector search.
- Projects needing integration with visualization tools and BI platforms via
  ODBC.
- Environments where developer familiarity with Redis is a priority.
- Applications requiring advanced search and query capabilities.

On the other hand, Valkey may be preferable for:

- Organizations prioritizing open-source licensing.
- High-throughput applications that can benefit from improved multi-threading.
- Environments where memory efficiency is critical.
- Projects where RDMA capabilities could provide performance advantages.
- Organizations with in-house expertise for support and maintenance.

## Future development

### Redis roadmap

Redis continues to focus on enhancing enterprise features while expanding AI
capabilities, particularly in vector database functionality for machine learning
applications.

The platform is also improving integration with business intelligence tools and
developing Redis Copilot with AI-assisted database management capabilities to
streamline operations.

[The return of Salvatore Sanfilippo](https://antirez.com/news/144) as an
evangelist in 2024 has renewed focus on the Redis core, potentially accelerating
innovation in the core product.

### Valkey roadmap

Valkey's development trajectory centers around performance optimization, with
significant work on multithreading improvements and memory efficiency.

The project is also investing in more scalable clustering systems, implementing
core changes to data types, and integrating Rust for improved memory safety.

According to Madelyn Olson, a principal engineer at AWS and Valkey maintainer,
the project is fundamentally rebuilding core components to better leverage
modern hardware capabilities, creating a database optimized for contemporary
computing environments.

## Final thoughts

The emergence of Valkey marks a pivotal moment for in-memory databases. What
began as a licensing response has evolved into a legitimate technical
alternative with distinct performance advantages.

While Redis offers maturity and comprehensive features, Valkey brings
open-source licensing and innovative hardware utilization.

As these projects evolve on separate paths, their competition will drive
innovation across the in-memory database space, benefiting the entire developer
ecosystem regardless of which solution they implement.

Thanks for reading!