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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonVictoriaMetrics  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 simplicityRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.A fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelDocument storeTime Series DBMSRDF storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.69
Rank#230  Overall
#9  RDF stores
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websitecloud.google.com/­datastorewww.circonus.com/solutions/time-series-database/rdf4j.orgvictoriametrics.com
Technical documentationcloud.google.com/­datastore/­docsdocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentationdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperGoogleCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.VictoriaMetrics
Initial release2008201720042018
Current releaseV0.10.20, January 2018v1.91, May 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++JavaGo
Server operating systemshostedLinuxLinux
OS X
Unix
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeschema-freeschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateyes, details hereyes 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.nonono
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query language (Circonus Analytics Query Language: CAQL)nono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
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
Java
PHP
Python
Server-side scripts infoStored proceduresusing Google App Engineyes, in Luayesno
TriggersCallbacks using the Google Apps Enginenoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosconfigurable replication factor, datacenter awarenoneSynchronous replication
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 nodesEventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
Google Cloud DatastoreIRONdbRDF4J infoformerly known as SesameVictoriaMetrics
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