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DBMS > AgensGraph vs. Google Cloud Datastore vs. Graph Engine vs. IRONdb vs. RDF4J

System Properties Comparison AgensGraph vs. Google Cloud Datastore vs. Graph Engine vs. IRONdb vs. RDF4J

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelGraph DBMS
Relational DBMS
Document storeGraph DBMS
Key-value store
Time Series DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#333  Overall
#30  Graph DBMS
#146  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score0.62
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score0.71
Rank#231  Overall
#9  RDF stores
Websitebitnine.net/­agensgraphcloud.google.com/­datastorewww.graphengine.iowww.circonus.com/solutions/time-series-database/rdf4j.org
Technical documentationbitnine.net/­documentationcloud.google.com/­datastore/­docswww.graphengine.io/­docs/­manualdocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentation
DeveloperBitnine Global Inc.GoogleMicrosoftCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20162008201020172004
Current release2.1, December 2018V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialOpen Source infoMIT LicensecommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC.NET and CC and C++Java
Server operating systemsLinux
OS X
Windows
hosted.NETLinuxLinux
OS X
Unix
Windows
Data schemedepending on used data modelschema-freeyesschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes, details hereyesyes infotext, numeric, histogramsyes
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 indexesyesyesnoyes
SQL infoSupport of SQLyesSQL-like query language (GQL)noSQL-like query language (Circonus Analytics Query Language: CAQL)no
APIs and other access methodsCypher Query Language
JDBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIHTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC
Java
JavaScript
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
F#
Visual Basic
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
PHP
Python
Server-side scripts infoStored proceduresyesusing Google App Engineyesyes, in Luayes
TriggersnoCallbacks using the Google Apps Enginenonoyes
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardinghorizontal partitioningAutomatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using Paxosconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 per node, eventual consistency across nodes
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnonoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes 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.nonoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
AgensGraphGoogle Cloud DatastoreGraph Engine infoformer name: TrinityIRONdbRDF4J infoformerly known as Sesame
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