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DBMS > Google Cloud Datastore vs. HugeGraph vs. OrientDB vs. Postgres-XL

System Properties Comparison Google Cloud Datastore vs. HugeGraph vs. OrientDB vs. Postgres-XL

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHugeGraph  Xexclude from comparisonOrientDB  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA fast-speed and highly-scalable Graph DBMSMulti-model DBMS (Document, Graph, Key/Value)Based on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelDocument storeGraph DBMSDocument store
Graph DBMS
Key-value store
Relational DBMS
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
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score3.19
Rank#93  Overall
#16  Document stores
#7  Graph DBMS
#14  Key-value stores
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websitecloud.google.com/­datastoregithub.com/­hugegraph
hugegraph.apache.org
orientdb.orgwww.postgres-xl.org
Technical documentationcloud.google.com/­datastore/­docshugegraph.apache.org/­docswww.orientdb.com/­docs/­last/­index.htmlwww.postgres-xl.org/­documentation
DeveloperGoogleBaiduOrientDB LTD; CallidusCloud; SAP
Initial release2008201820102014 infosince 2012, originally named StormDB
Current release0.93.2.29, March 202410 R1, October 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache version 2Open Source infoMozilla public license
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 languageJavaJavaC
Server operating systemshostedLinux
macOS
Unix
All OS with a Java JDK (>= JDK 6)Linux
macOS
Data schemeschema-freeyesschema-free infoSchema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")yes
Typing infopredefined data types such as float or dateyes, details hereyesyesyes
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.nononoyes infoXML type, but no XML query functionality
Secondary indexesyesyes infoalso supports composite index and range indexyesyes
SQL infoSupport of SQLSQL-like query language (GQL)noSQL-like query language, no joinsyes infodistributed, parallel query execution
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Groovy
Java
Python
.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresusing Google App Engineasynchronous Gremlin script jobsJava, Javascriptuser defined functions
TriggersCallbacks using the Google Apps EnginenoHooksyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infodepending on used storage backend, e.g. Cassandra and HBaseMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowvia hugegraph-sparkno infocould be achieved with distributed queriesno
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.Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyes infoedges in graphyes inforelationship in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDACID infoMVCC
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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissionsAccess rights for users and roles; record level security configurablefine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreHugeGraphOrientDBPostgres-XL
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