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

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

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonOrientDB  Xexclude from comparisonPostgres-XL  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMulti-model DBMS (Document, Graph, Key/Value)Based on PostgreSQL enhanced with MPP and write-scale-out cluster featuresDistributed, high-performance timeseries database
Primary database modelDocument storeDocument store
Graph DBMS
Key-value store
Relational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score3.25
Rank#89  Overall
#16  Document stores
#6  Graph DBMS
#13  Key-value stores
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Websitecloud.google.com/­datastoreorientdb.orgwww.postgres-xl.orgquasar.ai
Technical documentationcloud.google.com/­datastore/­docswww.orientdb.com/­docs/­last/­index.htmlwww.postgres-xl.org/­documentationdoc.quasar.ai/­master
DeveloperGoogleOrientDB LTD; CallidusCloud; SAPquasardb
Initial release200820102014 infosince 2012, originally named StormDB2009
Current release3.2.29, March 202410 R1, October 20183.14.1, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoMozilla public licensecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
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 languageJavaCC++
Server operating systemshostedAll OS with a Java JDK (>= JDK 6)Linux
macOS
BSD
Linux
OS X
Windows
Data schemeschema-freeschema-free infoSchema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")yesschema-free
Typing infopredefined data types such as float or dateyes, details hereyesyesyes infointeger and binary
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.nonoyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesyesyes infowith tags
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query language, no joinsyes infodistributed, parallel query executionSQL-like query language
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
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
HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.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
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresusing Google App EngineJava, Javascriptuser defined functionsno
TriggersCallbacks using the Google Apps EngineHooksyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replicationSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowno infocould be achieved with distributed queriesnowith Hadoop integration
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyes inforelationship in graphsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID infoMVCCACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoTransient mode
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles; record level security configurablefine grained access rights according to SQL-standardCryptographically strong user authentication and audit trail

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More resources
Google Cloud DatastoreOrientDBPostgres-XLQuasardb
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