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DBMS > Google Cloud Datastore vs. RDF4J vs. Realm vs. Sphinx vs. SwayDB

System Properties Comparison Google Cloud Datastore vs. RDF4J vs. Realm vs. Sphinx vs. SwayDB

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonRealm  Xexclude from comparisonSphinx  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionAutomatically 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.A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataOpen source search engine for searching in data from different sources, e.g. relational databasesAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelDocument storeRDF storeDocument storeSearch engineKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.74
Rank#222  Overall
#9  RDF stores
Score7.41
Rank#52  Overall
#8  Document stores
Score5.95
Rank#55  Overall
#5  Search engines
Score0.04
Rank#387  Overall
#61  Key-value stores
Websitecloud.google.com/­datastorerdf4j.orgrealm.iosphinxsearch.comswaydb.simer.au
Technical documentationcloud.google.com/­datastore/­docsrdf4j.org/­documentationrealm.io/­docssphinxsearch.com/­docs
DeveloperGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Realm, acquired by MongoDB in May 2019Sphinx Technologies Inc.Simer Plaha
Initial release20082004201420012018
Current release3.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open SourceOpen Source infoGPL version 2, commercial licence availableOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Scala
Server operating systemshostedLinux
OS X
Unix
Windows
Android
Backend: server-less
iOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyes infoRDF Schemasyesyesschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesnono
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.nonono
Secondary indexesyesyesyesyes infofull-text index on all search fieldsno
SQL infoSupport of SQLSQL-like query language (GQL)nonoSQL-like query language (SphinxQL)no
APIs and other access methodsgRPC (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
Proprietary protocol
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
.Net
Java infowith Android only
Objective-C
React Native
Swift
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Java
Kotlin
Scala
Server-side scripts infoStored proceduresusing Google App Engineyesno inforuns within the applications so server-side scripts are unnecessarynono
TriggersCallbacks using the Google Apps Engineyesyes infoChange Listenersnono
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosnonenonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoIsolation support depends on the API usedACIDnoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoin-memory storage is supported as wellyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoIn-Memory realmyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noyesnono

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More resources
Google Cloud DatastoreRDF4J infoformerly known as SesameRealmSphinxSwayDB
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