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DBMS > Amazon DocumentDB vs. Google Cloud Firestore vs. MarkLogic vs. PouchDB vs. SwayDB

System Properties Comparison Amazon DocumentDB vs. Google Cloud Firestore vs. MarkLogic vs. PouchDB vs. SwayDB

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonMarkLogic  Xexclude from comparisonPouchDB  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Operational and transactional Enterprise NoSQL databaseJavaScript DBMS with an API inspired by CouchDBAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelDocument storeDocument storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Document storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score7.85
Rank#51  Overall
#8  Document stores
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score2.28
Rank#115  Overall
#21  Document stores
Score0.00
Rank#382  Overall
#59  Key-value stores
Websiteaws.amazon.com/­documentdbfirebase.google.com/­products/­firestorewww.marklogic.compouchdb.comswaydb.simer.au
Technical documentationaws.amazon.com/­documentdb/­resourcesfirebase.google.com/­docs/­firestoredocs.marklogic.compouchdb.com/­guides
DeveloperGoogleMarkLogic Corp.Apache Software FoundationSimer Plaha
Initial release20192017200120122018
Current release11.0, December 20227.1.1, June 2019
License infoCommercial or Open Sourcecommercialcommercialcommercial inforestricted free version is availableOpen SourceOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaScriptScala
Server operating systemshostedhostedLinux
OS X
Windows
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeschema-freeschema-freeschema-free infoSchema can be enforcedschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesnono
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.nonoyesnono
Secondary indexesyesyesyesyes infovia viewsno
SQL infoSupport of SQLnonoyes infoSQL92nono
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
JavaScriptJava
Kotlin
Scala
Server-side scripts infoStored proceduresnoyes, Firebase Rules & Cloud Functionsyes infovia XQuery or JavaScriptView functions in JavaScriptno
Triggersnoyes, with Cloud Functionsyesyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infowith a proxy-based framework, named couchdb-loungenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replicationyesMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Using Cloud Dataflowyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsyesACID infocan act as a resource manager in an XA/JTA transactionnoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, with Range Indexesyesyes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Role-based access control at the document and subdocument levelsnono

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More resources
Amazon DocumentDBGoogle Cloud FirestoreMarkLogicPouchDBSwayDB
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