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DBMS > Google Cloud Datastore vs. IRONdb vs. RDF4J vs. TerarkDB vs. WakandaDB

System Properties Comparison Google Cloud Datastore vs. IRONdb vs. RDF4J vs. TerarkDB vs. WakandaDB

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonIRONdb  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTerarkDB  Xexclude from comparisonWakandaDB  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 key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDBWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument storeTime Series DBMSRDF storeKey-value storeObject oriented DBMS
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
Score0.08
Rank#367  Overall
#56  Key-value stores
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websitecloud.google.com/­datastorewww.circonus.com/solutions/time-series-database/rdf4j.orggithub.com/­bytedance/­terarkdbwakanda.github.io
Technical documentationcloud.google.com/­datastore/­docsdocs.circonus.com/irondb/category/getting-startedrdf4j.org/­documentationbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKcwakanda.github.io/­doc
DeveloperGoogleCirconus LLC.Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.ByteDance, originally TerarkWakanda SAS
Initial release20082017200420162012
Current releaseV0.10.20, January 20182.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercial inforestricted open source version availableOpen Source infoAGPLv3, extended commercial license available
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 languageC and C++JavaC++C++, JavaScript
Server operating systemshostedLinuxLinux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyes infoRDF Schemasschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyes infotext, numeric, histogramsyesnoyes
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 indexesyesnoyesno
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query language (Circonus Analytics Query Language: CAQL)nonono
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
C++ API
Java API
RESTful HTTP API
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
C++
Java
JavaScript
Server-side scripts infoStored proceduresusing Google App Engineyes, in Luayesnoyes
TriggersCallbacks using the Google Apps Enginenoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodenonenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosconfigurable replication factor, datacenter awarenonenonenone
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 consistency per node, eventual consistency across nodesImmediate 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 usednoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nononoyes

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More resources
Google Cloud DatastoreIRONdbRDF4J infoformerly known as SesameTerarkDBWakandaDB
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