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DBMS > CouchDB vs. Google Cloud Datastore vs. RDF4J vs. Spark SQL vs. SwayDB

System Properties Comparison CouchDB vs. Google Cloud Datastore vs. RDF4J vs. Spark SQL vs. SwayDB

Editorial information provided by DB-Engines
NameCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSpark SQL  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Spark SQL is a component on top of 'Spark Core' for structured data processingAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelDocument storeDocument storeRDF storeRelational DBMSKey-value store
Secondary database modelsSpatial DBMS infousing the Geocouch extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.30
Rank#47  Overall
#7  Document stores
Score4.36
Rank#72  Overall
#12  Document stores
Score0.74
Rank#222  Overall
#9  RDF stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#387  Overall
#61  Key-value stores
Websitecouchdb.apache.orgcloud.google.com/­datastorerdf4j.orgspark.apache.org/­sqlswaydb.simer.au
Technical documentationdocs.couchdb.org/­en/­stablecloud.google.com/­datastore/­docsrdf4j.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Apache Software FoundationSimer Plaha
Initial release20052008200420142018
Current release3.3.3, December 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache version 2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache 2.0Open Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangJavaScalaScala
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
hostedLinux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyes infoRDF Schemasyesschema-free
Typing infopredefined data types such as float or datenoyes, details hereyesyesno
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 indexesyes infovia viewsyesyesnono
SQL infoSupport of SQLnoSQL-like query language (GQL)noSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP/JSON APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
ODBC
Supported programming languagesC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
Java
Python
R
Scala
Java
Kotlin
Scala
Server-side scripts infoStored proceduresView functions in JavaScriptusing Google App Engineyesnono
TriggersyesCallbacks using the Google Apps Engineyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoimproved architecture with release 2.0Shardingnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using Paxosnonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a single document possibleACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoIsolation support depends on the API usednoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nonono

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CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"Google Cloud DatastoreRDF4J infoformerly known as SesameSpark SQLSwayDB
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