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DBMS > Couchbase vs. Firebase Realtime Database vs. Graphite vs. Microsoft Azure Cosmos DB

System Properties Comparison Couchbase vs. Firebase Realtime Database vs. Graphite vs. Microsoft Azure Cosmos DB

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Editorial information provided by DB-Engines
NameCouchbase infoOriginally called Membase  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGraphite  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparison
DescriptionA distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile databaseCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Data logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperGlobally distributed, horizontally scalable, multi-model database service
Primary database modelDocument storeDocument storeTime Series DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsKey-value store infooriginating from the former Membase product and supporting the Memcached protocol
Spatial DBMS infousing the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.30
Rank#36  Overall
#5  Document stores
Score14.29
Rank#39  Overall
#6  Document stores
Score4.57
Rank#73  Overall
#5  Time Series DBMS
Score29.04
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Websitewww.couchbase.comfirebase.google.com/­products/­realtime-databasegithub.com/­graphite-project/­graphite-webazure.microsoft.com/­services/­cosmos-db
Technical documentationdocs.couchbase.comfirebase.google.com/­docs/­databasegraphite.readthedocs.iolearn.microsoft.com/­azure/­cosmos-db
DeveloperCouchbase, Inc.Google infoacquired by Google 2014Chris DavisMicrosoft
Initial release2011201220062014
Current releaseServer: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023
License infoCommercial or Open SourceOpen Source infoBusiness Source License (BSL 1.1); Commercial licenses also availablecommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++, Go and ErlangPython
Server operating systemsLinux
OS X
Windows
hostedLinux
Unix
hosted
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesNumeric data onlyyes infoJSON types
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.nono
Secondary indexesyesyesnoyes infoAll properties auto-indexed by default
SQL infoSupport of SQLSQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use casesnonoSQL-like query language
APIs and other access methodsCLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data
Android
iOS
JavaScript API
RESTful HTTP API
HTTP API
Sockets
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
Supported programming languages.Net
C
Go
Java
JavaScript infoNode.js
Kotlin
PHP
Python
Ruby
Scala
Java
JavaScript
Objective-C
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
Server-side scripts infoStored proceduresFunctions and timers in JavaScript and UDFs in Java, Python, SQL++limited functionality with using 'rules'noJavaScript
Triggersyes infovia the TAP protocolCallbacks are triggered when data changesnoJavaScript
Partitioning methods infoMethods for storing different data on different nodesAutomatic ShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infoincluding cross data center replication
Source-replica replication
noneyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonowith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infoselectable on a per-operation basis
Eventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
noneBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnoMulti-item ACID transactions with snapshot isolation within a partition
Concurrency infoSupport for concurrent manipulation of datayesyesyes infolockingyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoEphemeral buckets
User concepts infoAccess controlUser and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.yes, based on authentication and database rulesnoAccess rights can be defined down to the item level

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More resources
Couchbase infoOriginally called MembaseFirebase Realtime DatabaseGraphiteMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB
DB-Engines blog posts

Couchbase climbs up the DB-Engines Ranking, increasing its popularity by 10% every month
2 June 2014, Matthias Gelbmann

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Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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