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DBMS > Datomic vs. Dragonfly vs. GridDB vs. Microsoft Azure Cosmos DB vs. Redis

System Properties Comparison Datomic vs. Dragonfly vs. GridDB vs. Microsoft Azure Cosmos DB vs. Redis

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonDragonfly  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonRedis  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceScalable in-memory time series database optimized for IoT and Big DataGlobally distributed, horizontally scalable, multi-model database servicePopular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments infoRedis focuses on performance so most of its design decisions prioritize high performance and very low latencies.
Primary database modelRelational DBMSKey-value storeTime Series DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Key-value store infoMultiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMSDocument store infowith RedisJSON
Graph DBMS infowith RedisGraph
Spatial DBMS
Search engine infowith RediSearch
Time Series DBMS infowith RedisTimeSeries
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.41
Rank#266  Overall
#38  Key-value stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score29.04
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score157.80
Rank#6  Overall
#1  Key-value stores
Websitewww.datomic.comgithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
griddb.netazure.microsoft.com/­services/­cosmos-dbredis.com
redis.io
Technical documentationdocs.datomic.comwww.dragonflydb.io/­docsdocs.griddb.netlearn.microsoft.com/­azure/­cosmos-dbdocs.redis.com/­latest/­index.html
redis.io/­docs
DeveloperCognitectDragonflyDB team and community contributorsToshiba CorporationMicrosoftRedis project core team, inspired by Salvatore Sanfilippo infoDevelopment sponsored by Redis Inc.
Initial release20122023201320142009
Current release1.0.6735, June 20231.0, March 20235.1, August 20227.2.5, May 2024
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoBSL 1.1Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infosource-available extensions (modules), commercial licenses for Redis Enterprise
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.
Implementation languageJava, ClojureC++C++C
Server operating systemsAll OS with a Java VMLinuxLinuxhostedBSD
Linux
OS X
Windows infoported and maintained by Microsoft Open Technologies, Inc.
Data schemeyesscheme-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesstrings, hashes, lists, sets, sorted sets, bit arraysyes infonumerical, string, blob, geometry, boolean, timestampyes infoJSON typespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononono
Secondary indexesyesnoyesyes infoAll properties auto-indexed by defaultyes infowith RediSearch module
SQL infoSupport of SQLnonoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query languagewith RediSQL module
APIs and other access methodsRESTful HTTP APIProprietary protocol infoRESP - REdis Serialization ProtocolJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
proprietary protocol infoRESP - REdis Serialization Protocol
Supported programming languagesClojure
Java
C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Server-side scripts infoStored proceduresyes infoTransaction FunctionsLuanoJavaScriptLua; Redis Functions coming in Redis 7 (slides and Github)
TriggersBy using transaction functionspublish/subscribe channels provide some trigger functionalityyesJavaScriptpublish/subscribe channels provide some trigger functionality; RedisGears
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding infoImplicit feature of the cloud serviceSharding infoAutomatic hash-based sharding with support for hash-tags for manual sharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSource-replica replicationSource-replica replicationyes infoImplicit feature of the cloud serviceMulti-source replication infowith Redis Enterprise Pack
Source-replica replication infoChained replication is supported
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobswith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*through RedisGears
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate consistency within container, eventual consistency across containersBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of command blocks and scriptsACID at container levelMulti-item ACID transactions with snapshot isolation within a partitionAtomic execution of command blocks and scripts and optimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logs
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesyesyes
User concepts infoAccess controlnoPassword-based authenticationAccess rights for users can be defined per databaseAccess rights can be defined down to the item levelAccess Control Lists (ACLs): redis.io/­docs/­management/­security/­acl
LDAP and Role-Based Access Control (RBAC) for Redis Enterprise
Mutual TLS authentication: redis.io/­docs/­management/­security/­encryption
Password-based authentication
More information provided by the system vendor
DatomicDragonflyGridDBMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBRedis
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.
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DatomicDragonflyGridDBMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBRedis
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