Redis

Redis (; Remote Dictionary Server) is an in-memory key–value database, used as a distributed cache and message broker, with optional durability. Because it holds all data in memory and because of its design, Redis offers low- latency reads and writes, making it particularly suitable for use cases that require a cache. Redis is the most popular NoSQL database, and one of the most popular databases overall.

The project was developed and maintained by Salvatore Sanfilippo, starting in 2009. From 2015 until 2020, he led a project core team sponsored by Redis Ltd. Salvatore Sanfilippo left Redis as the maintainer in 2020. In 2021 Redis Labs dropped the Labs from its name and now is known simply as "Redis".

In 2018, some modules for Redis adopted a modified Apache 2.0 with a Commons Clause. In 2024, the main Redis code switched from the open-source BSD-3 license to being dual-licensed under the Redis Source Available License v2 and the Server Side Public License v1. On May 1, 2025, Redis became tri-licensed beginning with version 8.0, with the GNU Affero General Public License as the third option.

History

The name ''Redis'' means Remote Dictionary Server. The Redis project began when Salvatore Sanfilippo, nicknamed ''antirez'', the original developer of Redis, was trying to improve the scalability of his Italian startup, developing a real-time web log analyzer. After encountering significant problems in scaling some types of workloads using traditional database systems, Sanfilippo began in 2009 to prototype a first proof of concept version of Redis in Tcl. Later Sanfilippo translated that prototype to the C language and implemented the first data type, the list. After a few weeks of using the project internally with success, Sanfilippo decided to open source it, announcing the project on Hacker News. The project began to get traction, particularly among the Ruby community, with GitHub and Instagram being among the first companies adopting it.

Sanfilippo was hired by VMware in March 2010.

In May 2013, Redis was sponsored by Pivotal Software (a VMware spin-off).

In June 2015, development became sponsored by Redis Ltd.

In August 2018, to control usage of the software by managed cloud providers without adequate compensation, Redis Ltd. announced that it would relicense the optional Redis modules from the GNU Affero General Public License (AGPL) to the Apache License, but subject to an addendum known as the " Commons Clause" that restricts commercial usage. This made the modules source-available and no longer free software. The core Redis software remained under a BSD license, with Redis Ltd. committing to maintaining these terms.

In October 2018, Redis 5.0 was released, introducing Redis Stream – a new data structure that allows storage of multiple fields and string values with an automatic, time-based sequence at a single key.

In February 2019, citing confusion over the licensing terms, the Apache License with Commons Clause licensing terms for Redis modules was replaced with the "Redis Source Available License" (RSAL), which explicitly prohibits commercial use of the modules as part of "a database, a caching engine, a stream processing engine, a search engine, an indexing engine or an ML/DL/AI serving engine." The last revision of the modules under a free and open source license were forked by community members as the GoodFORM project.

In June 2020, Salvatore Sanfilippo stepped down as Redis' sole maintainer. Sanfilippo was succeeded by Yossi Gottlieb and Oran Agra.

In March 2024, Redis Ltd. announced that beginning with version 7.4, the core Redis software would be relicensed under the RSAL and Server Side Public License (SSPL), both of which are source-available and non-free. The Linux Foundation subsequently announced that it would fork the last BSD-licensed version of Redis as Valkey. In May 2025, Redis Ltd. announced that it would change the license again to the AGPL beginning on version 8.0, citing that that forks had achieved their goal of creating a "level playing field" of differentiated products, and that Redis has achieved "record growth" since the change in license.

Differences from other database systems

Redis popularized the idea of a system that can be considered a store and a cache at the same time. It was designed so that data is always modified and read from the main computer memory, but also stored on disk in a format that is unsuitable for random data access. The formatted data is only reconstructed into memory once the system restarts.

Redis also provides a data model that is very unusual compared to a relational database management system (RDBMS). User commands do not describe a query to be executed by the database engine but rather specific operations that are performed on given abstract data types. Therefore data must be stored in a way which is suitable later for fast retrieval. The retrieval is done without help from the database system in form of secondary indexes, aggregations or other common features of traditional RDBMS. The Redis implementation makes heavy use of the fork system call, to duplicate the process holding the data, so that the parent process continues to serve clients while the child process writes the in-memory data to disk.

Popularity

According to monthly DB-Engines rankings, Redis is often the most popular key–value database. Redis has also been ranked the #4 NoSQL database in user satisfaction and market presence based on user reviews, the most popular NoSQL database in containers, and the #4 Data store of 2019 by ranking website stackshare.io. It was voted most loved database in the Stack Overflowbr>Developer Survey
each year from 2017 to 2021, however, it has since fallen to sixth place.

Supported languages

Since version 2.6, Redis features server-side scripting in the language Lua.

Many programming languages have Redis language bindings on the client side, including: ActionScript, C, C++, C#, Chicken, Clojure, Common Lisp, Crystal, D, Dart, Delphi, Elixir, Erlang, Go, Haskell, Haxe, Io, Java, Nim, JavaScript ( Node.js), Julia, Lua, Objective-C, OCaml, Perl, PHP, Pure Data, Python, R, Racket, Ruby, Rust, Scala, Smalltalk, Swift, and Tcl. Several client software programs exist in these languages.

Redis data types, processing engines, and capabilities

Redis maps keys to types of values. An important difference between Redis and other structured storage systems is that Redis supports not only strings, but also abstract data types:

String
- A Redis string is the most basic Redis data type. It holds a sequence of bytes. A string may represent a text, an integer value, a floating-point value, a serialized object, or anything else.

JSON
- The Redis JSON data type provides JavaScript Object Notation (JSON) support for Redis. It lets users store, retrieve, and update JSON documents. A JSON document can be queried and manipulated using JSONPath expressions. JSON works seamlessly with the Redis Query Engine to let users index and query JSON documents.

Hash
A Redis hash is a collection of fields, each field is a name-value string pair. Users can use hashes to represent flat objects and to store groupings of counters, among other things. Expiration time or a time-to-live can be set for each hash field. Hash works seamlessly with the Redis Query Engine to let users index and query hashes.

Redis Query Engine
The Redis Query Engine allows users to use Redis as a document database, a vector database, a secondary index, and a search engine. With Redis Query Engine, users can define indexes for hash and JSON documents, and use a rich query language for vector search, full-text search, geospatial queries, and aggregations.

List
A Redis list is a list of strings, sorted by insertion order. Lists are great for stacks, queues, and for queue management and worker systems.

Set
A Redis set is an unordered collection of unique strings (members). Sets can be used to track unique items (e.g., track all unique IP addresses accessing a given blog post), represent relations (e.g., the set of all users with a given role). Redis also supports common set operations such as intersection, union, and difference.

Sorted Set
A Redis sorted set is similar to a set, but each member is associated with a score. When more than one member has the same score, the members are ordered lexicographically. Some use cases for sorted sets include leaderboards and sliding-window rate limiters.

Vector Set
A Redis vector set is a data type similar to a sorted set, but instead of a score, each member is associated with a vector embedding. Users can add items to a vector set and then retrieve the members that are the most similar to a specified vector embedding or the vector embedding of an existing member.

Geospatial Index
Redis Geospatial indexes let users store coordinates and search for them. This data structure is useful for finding nearby points within a given radius or bounding box.

Bitmap
Redis bitmaps provide bit-oriented operations on a bit array. Users can get bits, set bits, and perform bitwise operations between bitmaps. Bitmaps are often used to efficiently manage memberships or permissions, where each bit represents a particular member.

Bitfield
Redis bitfields let users set, increment, and get integer values of arbitrary bit length - from unsigned 1-bit integers to signed 63-bit integers. Bitfields are often used to efficiently manage arrays of limited-range counters or numerical values.

HyperLogLog
Redis HyperLogLog is a Redis probabilistic data structure used for approximating the cardinality of a stream (i.e., the number of unique elements).

Bloom filter
Bloom filter is a Redis probabilistic data structure used for checking if a given value is present in a stream.

Cuckoo filter
Cuckoo filter, just like Bloom filter, is a Redis probabilistic data structure for checking if a given value is present in a stream, while also allowing limited counting and deletions.

Top-k
Top-k is a Redis probabilistic data structure used for tracking the most frequent values in a stream.

Count-min sketch
Count–min sketch is a Redis probabilistic data structure used for estimating how many times a given value appears in a stream.

t-digest
t-digest is a Redis probabilistic data structure used for estimating which fraction / how many values in a stream are smaller than a given value, or which value is smaller than ''p'' percent of the values in a stream (the ''p''-percentile value).

Time Series
A Redis time series allows storing and querying a series of timetagged data points (samples).

Pub/Sub
Redis Pub/Sub (short for publish/subscribe) is a lightweight messaging capability. Publishers send messages to a channel, and subscribers receive messages from that channel.

Stream
A Redis stream is a data structure that acts like an append-only log. Each stream entry consists of name-value string pairs, similar to a hash. Streams support multiple consumption strategies, where consumers can pop entries, consume entries by range, or listen to entries. Consumer groups allow multiple workers to retrieve different stream entries in order to scale message processing.

Transactions
A Redis transaction allows the execution of a group of commands in a single step. A request sent by another client will never be served during the execution of a transaction. This guarantees that the commands are executed as a single isolated operation.

Programmability
Redis users can upload and execute Lua scripts on the server. Scripts can employ programmatic control structures and use most of the commands while executing to access the database. Because scripts are executed on the server, reading and writing data from scripts is very efficient. Functions provide the same core functionality as scripts but are first-class software artifacts of the database. Redis manage
functions
as an integral part of the database and ensures their availability via data persistence and replication.

Persistence

Redis typically holds the whole dataset in memory. Versions up to 2.4 could be configured to use what they refer to as virtual memory in which some of the dataset is stored on disk, but this feature is deprecated. Persistence in Redis can be achieved through two different methods. First by snapshotting, where the dataset is asynchronously transferred from memory to disk at regular intervals as a binary dump, using the Redis RDB Dump File Format. Alternatively by journaling, where a record of each operation that modifies the dataset is added to an append-only file (AOF) in a background process. Redis can rewrite the append-only file in the background to avoid an indefinite growth of the journal. Journaling was introduced in version 1.1 and is generally considered the safer approach.

By default, Redis writes data to a file system at least every 2 seconds, with more or less robust options available if needed. In the case of a complete system failure on default settings, only a few seconds of data would be lost.

Replication

Redis supports master–replica replication. Data from any Redis server can replicate to any number of replicas. A replica may be a master to another replica. This allows Redis to implement a single-rooted replication tree. Redis replicas can be configured to accept writes, permitting intentional and unintentional inconsistency between instances. The publish–subscribe feature is fully implemented, so a client of a replica may subscribe to a channel and receive a full feed of messages published to the master, anywhere up the replication tree. Replication is useful for read (but not write) scalability or data redundancy.

Performance

When the durability of data is not needed, the in-memory nature of Redis allows it to perform well compared to database systems that write every change to disk before considering a transaction committed. Redis operates as a single process and is single-threaded or double-threaded when it rewrites the AOF (append-only file). Thus, a single Redis instance cannot use parallel execution of tasks such as stored procedures.

Clustering

Redis introduced clustering in April 2015 with the release of version 3.0. The cluster specification implements a subset of Redis commands: all single-key commands are available, multi-key operations (commands related to unions and intersections) are restricted to keys belonging to the same node, and commands related to database selection operations are unavailable. A Redis cluster can scale up to 1,000 nodes, achieve "acceptable" write safety and to continue operations when some nodes fail.

Use cases

Due to the nature of the database design, typical use cases are session caching, full page cache, message queue applications, leaderboards and counting among others. The publish–subscribe messaging paradigm allows real-time communication between servers.

Amazon Web Services offers a managed Redis service called ElastiCache for Redis, Google offers a managed Redis service called Cloud Memorystore, Microsoft offers Azure Cache for Redis in Azure, and Alibaba offers ApsaraDB for Redis in Alibaba Cloud.

Users

Redis has been used by companies including Twitter, Airbnb, Tinder, Yahoo, Adobe, Hulu, Amazon and OpenAI.

See also

* Conflict-free replicated data type
* Memcached
* Infinispan
* Valkey

References

Further reading

* Isabel Drost and Jan Lehnard (29 October 2009)
Happenings: NoSQL Conference, Berlin
The H
Slides
for the Redis presentation


* Billy Newport (IBM):
Evolving the Key/Value Programming Model to a Higher Level
Qcon Conference 2009 San Francisco.
* A Mishra:

.
* E. Mouzakitis:
Monitoring Redis Performance

External links

*

Valkey: Ongoing development home of the original BSD-licensed Redis software

{{DEFAULTSORT:Redis
C (programming language) software
Database caching
Database management systems
Distributed computing architecture
Key-value databases
Lua (programming language)-scriptable software
NoSQL
Software using the Server Side Public License
Structured storage
In-memory database management systems