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DBMS > Google Cloud Datastore vs. IRONdb vs. MonetDB vs. RDF4J

System Properties Comparison Google Cloud Datastore vs. IRONdb vs. MonetDB vs. RDF4J

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonIRONdb  Xexclude from comparisonMonetDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityA relational database management system that stores data in columnsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument storeTime Series DBMSRelational DBMSRDF store
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score1.72
Rank#145  Overall
#67  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitecloud.google.com/­datastorewww.circonus.com/solutions/time-series-database/www.monetdb.orgrdf4j.org
Technical documentationcloud.google.com/­datastore/­docsdocs.circonus.com/irondb/category/getting-startedwww.monetdb.org/­Documentationrdf4j.org/­documentation
DeveloperGoogleCirconus LLC.MonetDB BVSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2008201720042004
Current releaseV0.10.20, January 2018Dec2023 (11.49), December 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMozilla Public License 2.0Open Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++CJava
Server operating systemshostedLinuxFreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Unix
Windows
Data schemeschema-freeschema-freeyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyes, details hereyes infotext, numeric, histogramsyesyes
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.nono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query language (Circonus Analytics Query Language: CAQL)yes infoSQL 2003 with some extensionsno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP APIJDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Java
PHP
Python
Server-side scripts infoStored proceduresusing Google App Engineyes, in Luayes, in SQL, C, Ryes
TriggersCallbacks using the Google Apps Enginenoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeSharding via remote tablesnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosconfigurable replication factor, datacenter awarenone infoSource-replica replication available in experimental statusnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
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 consistency per node, eventual consistency across nodes
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standardno

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More resources
Google Cloud DatastoreIRONdbMonetDBRDF4J infoformerly known as Sesame
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