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DBMS > Dragonfly vs. Google Cloud Datastore vs. Google Cloud Firestore vs. RDF4J

System Properties Comparison Dragonfly vs. Google Cloud Datastore vs. Google Cloud Firestore vs. RDF4J

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Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformCloud 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.RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelKey-value storeDocument storeDocument storeRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
Score4.47
Rank#76  Overall
#12  Document stores
Score7.85
Rank#51  Overall
#8  Document stores
Score0.69
Rank#230  Overall
#9  RDF stores
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
cloud.google.com/­datastorefirebase.google.com/­products/­firestorerdf4j.org
Technical documentationwww.dragonflydb.io/­docscloud.google.com/­datastore/­docsfirebase.google.com/­docs/­firestorerdf4j.org/­documentation
DeveloperDragonflyDB team and community contributorsGoogleGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2023200820172004
Current release1.0, March 2023
License infoCommercial or Open SourceOpen Source infoBSL 1.1commercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemsLinuxhostedhostedLinux
OS X
Unix
Windows
Data schemescheme-freeschema-freeschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyes, details hereyesyes
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 indexesnoyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)nono
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC
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
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Java
PHP
Python
Server-side scripts infoStored proceduresLuausing Google App Engineyes, Firebase Rules & Cloud Functionsyes
Triggerspublish/subscribe channels provide some trigger functionalityCallbacks using the Google Apps Engineyes, with Cloud Functionsyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using PaxosMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud DataflowUsing Cloud Dataflowno
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 pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsyesACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlPassword-based authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.no

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More resources
DragonflyGoogle Cloud DatastoreGoogle Cloud FirestoreRDF4J infoformerly known as Sesame
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