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DBMS > Google Cloud Datastore vs. HBase vs. IRONdb vs. Stardog

System Properties Comparison Google Cloud Datastore vs. HBase vs. IRONdb vs. Stardog

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHBase  Xexclude from comparisonIRONdb  Xexclude from comparisonStardog  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 PlatformWide-column store based on Apache Hadoop and on concepts of BigTableA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelDocument storeWide column storeTime Series DBMSGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score27.97
Rank#26  Overall
#2  Wide column stores
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Websitecloud.google.com/­datastorehbase.apache.orgwww.circonus.com/solutions/time-series-database/www.stardog.com
Technical documentationcloud.google.com/­datastore/­docshbase.apache.org/­book.htmldocs.circonus.com/irondb/category/getting-starteddocs.stardog.com
DeveloperGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetCirconus LLC.Stardog-Union
Initial release2008200820172010
Current release2.3.4, January 2021V0.10.20, January 20187.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
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 languageJavaC and C++Java
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
LinuxLinux
macOS
Windows
Data schemeschema-freeschema-free, schema definition possibleschema-freeschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyes, details hereoptions to bring your own types, AVROyes 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 infoImport/export of XML data possible
Secondary indexesyesnonoyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLSQL-like query language (GQL)noSQL-like query language (Circonus Analytics Query Language: CAQL)Yes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
HTTP APIGraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresusing Google App Engineyes infoCoprocessors in Javayes, in Luauser defined functions and aggregates, HTTP Server extensions in Java
TriggersCallbacks using the Google Apps Engineyesnoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic, metric affinity per nodenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication
Source-replica replication
configurable replication factor, datacenter awareMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesnono
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 or Eventual ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsSingle row ACID (across millions of columns)noACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnoAccess rights for users and roles

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More resources
Google Cloud DatastoreHBaseIRONdbStardog
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