Compare the Top Key-Value Databases for Cloud as of October 2026

What are Key-Value Databases for Cloud?

Key-value databases are a type of NoSQL database that store data as pairs, where each unique key is associated with a value. This structure is simple and highly flexible, making key-value databases ideal for scenarios requiring fast access to data, such as caching, session management, and real-time applications. In these databases, the key acts as a unique identifier for retrieving or storing the value, which can be any type of data—strings, numbers, objects, or even binary data. Key-value stores are known for their scalability, performance, and ability to handle high volumes of read and write operations with low latency. These databases are particularly useful for applications that require quick lookups or high availability, such as online retail platforms, social networks, and recommendation systems. Compare and read user reviews of the best Key-Value Databases for Cloud currently available using the table below. This list is updated regularly.

  • 1
    Dragonfly

    Dragonfly

    DragonflyDB

    Dragonfly is a high-throughput key-value database compatible with the Redis and Valkey APIs. It supports strings, hashes, lists, sets, sorted sets, streams, JSON, and more, so applications built on Redis clients run on Dragonfly without code changes. Its multi-threaded, shared-nothing design processes requests across all CPU cores in parallel, sustaining up to 6 million operations per second per node with consistent low latency under load. The Dashtable data structure reduces memory overhead by up to 40%, letting teams store more keys on less hardware. Snapshotting runs without the memory spikes of fork-based persistence, so large datasets stay stable during backups. Dragonfly handles very large datasets on a single node before clustering is needed, which simplifies operations. Run it self-hosted or fully managed on Dragonfly Cloud.
    Starting Price: Free
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  • 2
    Couchbase

    Couchbase

    Couchbase

    Couchbase’s operational data platform for AI is a scalable foundation for enterprise operational, analytical, mobile and AI workloads that replaces legacy infrastructure and data services. Bring your data to life in new ways with Couchbase’s enterprise data partnership: launch game-changing customer experiences, explore the infinite possibilities of AI, scale your global operations, and move your data from the cloud to the edge, and beyond. Couchbase’s operational data platform for AI eliminates fragmented tech stacks, so teams can stay innovative and agile, with less risk and lower cost of ownership. With enterprise partnership and scalable, AI-ready technology, Couchbase turns your data into the foundation for your next breakthrough.
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  • 3
    InterSystems IRIS

    InterSystems IRIS

    InterSystems

    InterSystems IRIS is a complete cloud-first data platform that includes a multi-model transactional data management engine, an application development platform, and interoperability engine, and an open analytics platform. It is the next generation of our proven data management software.It includes the capabilities of InterSystems Cache and Ensemble, plus a wealth of exciting new capabilities to make it easy to build and deploy cloud based, analytics-intensive enterprise applications with even greater performance and scalability. InterSystems IRIS provides a set of APIs to operate with transactional persistent data simultaneously: key-value, relational, object, document, multidimensional. Data can be managed by SQL, Java, node.js, .NET, C++, Python, and native server-side ObjectScript language. InterSystems IRIS includes
  • 4
    eXtremeDB

    eXtremeDB

    McObject

    How is platform independent eXtremeDB different? - Hybrid data storage. Unlike other IMDS, eXtremeDB can be all-in-memory, all-persistent, or have a mix of in-memory tables and persistent tables - Active Replication Fabric™ is unique to eXtremeDB, offering bidirectional replication, multi-tier replication (e.g. edge-to-gateway-to-gateway-to-cloud), compression to maximize limited bandwidth networks and more - Row & Columnar Flexibility for Time Series Data supports database designs that combine row-based and column-based layouts, in order to best leverage the CPU cache speed - Embedded and Client/Server. Fast, flexible eXtremeDB is data management wherever you need it, and can be deployed as an embedded database system, and/or as a client/server database system -A hard real-time deterministic option in eXtremeDB/rt Designed for use in resource-constrained, mission-critical embedded systems. Found in everything from routers to satellites to trains to stock markets worldwide
  • 5
    InterSystems Caché
    InterSystems Caché® is a high-performance database that powers transaction processing applications around the world. It is used for everything from mapping a billion stars in the Milky Way, to processing a billion equity trades in a day, to managing smart energy grids. Caché is a multi-model (object, relational, key-value) DBMS and application server developed by InterSystems. InterSystems Caché provides several APIs to operate with same data simultaneously: key-value, relational, object, document, multi-dimensional. Data can be managed via SQL, Java, node.js, .NET, C++, Python. Caché also provides an application server which hosts web apps (CSP), REST, SOAP, web sockets and other types of TCP access for Caché data.
  • 6
    ScyllaDB

    ScyllaDB

    ScyllaDB

    ScyllaDB is the database for data-intensive apps that require high performance and low latency. It enables teams to harness the ever-increasing computing power of modern infrastructures – eliminating barriers to scale as data grows. Unlike any other database, ScyllaDB is a distributed NoSQL database fully compatible with Apache Cassandra and Amazon DynamoDB, yet is built with deep architectural advancements that enable exceptional end-user experiences at radically lower costs. Over 400 game-changing companies like Disney+ Hotstar, Expedia, FireEye, Discord, Zillow, Starbucks, Comcast, and Samsung use ScyllaDB for their toughest database challenges. ScyllaDB is available as free open source software, a fully-supported enterprise product, and a fully managed database-as-a-service (DBaaS) on multiple cloud providers.
  • 7
    Symas LMDB

    Symas LMDB

    Symas Corporation

    Symas LMDB is an extraordinarily fast, memory-efficient database we developed for the OpenLDAP Project. With memory-mapped files, it has the read performance of a pure in-memory database while retaining the persistence of standard disk-based databases. Bottom line, with only 32KB of object code, LMDB may seem tiny. But it’s the right 32KB. Compact and efficient are two sides of a coin; that’s part of what makes LMDB so powerful. Symas offers fixed-price commercial support to those using LMDB in your applications. Development occurs in the OpenLDAP Project‘s git repo in the mdb.master branch. Symas LMDB has been written about, talked about, and utilized in a variety of impressive products and publications.
  • 8
    LevelDB

    LevelDB

    Google

    LevelDB is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values. Keys and values are arbitrary byte arrays. Data is stored sorted by key. Callers can provide a custom comparison function to override the sort order. Multiple changes can be made in one atomic batch. Users can create a transient snapshot to get a consistent view of data. Forward and backward iteration is supported over the data. Data is automatically compressed using the Snappy compression library. External activity (file system operations etc.) is relayed through a virtual interface so users can customize the operating system interactions. We use a database with a million entries. Each entry has a 16 byte key, and a 100 byte value. Values used by the benchmark compress to about half their original size. We list the performance of reading sequentially in both the forward and reverse direction, and also the performance of a random lookup.
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