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DBMS > Google Cloud Datastore vs. JSqlDb vs. Microsoft Azure Table Storage vs. OrientDB vs. Spark SQL

System Properties Comparison Google Cloud Datastore vs. JSqlDb vs. Microsoft Azure Table Storage vs. OrientDB vs. Spark SQL

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonJSqlDb  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOrientDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
JSqlDB 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 PlatformJavaScript Query Language Database, stores JavaScript objects and primitivesA Wide Column Store for rapid development using massive semi-structured datasetsMulti-model DBMS (Document, Graph, Key/Value)Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeDocument store
Object oriented DBMS
Wide column storeDocument store
Graph DBMS
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Score3.19
Rank#93  Overall
#16  Document stores
#7  Graph DBMS
#14  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitecloud.google.com/­datastorejsqldb.org (offline)azure.microsoft.com/­en-us/­services/­storage/­tablesorientdb.orgspark.apache.org/­sql
Technical documentationcloud.google.com/­datastore/­docswww.orientdb.com/­docs/­last/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleKonrad von BackstromMicrosoftOrientDB LTD; CallidusCloud; SAPApache Software Foundation
Initial release20082018201220102014
Current release0.8, December 20183.2.29, March 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen SourcecommercialOpen Source infoApache version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScala
Server operating systemshostedLinux
macOS
Windows
hostedAll OS with a Java JDK (>= JDK 6)Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeschema-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 herenoyesyesyes
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.nonononono
Secondary indexesyesnonoyesno
SQL infoSupport of SQLSQL-like query language (GQL)nonoSQL-like query language, no joinsSQL-like DML and DDL statements
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APITinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScript.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresusing Google App Enginefunctions in JavaScriptnoJava, Javascriptno
TriggersCallbacks using the Google Apps EnginenonoHooksno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud serviceShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosnoneyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono infocould be achieved with distributed queries
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
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonoyes inforelationship in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsoptimistic lockingACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing RocksDByesyesyes
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)Access rights based on private key authentication or shared access signaturesAccess rights for users and roles; record level security configurableno

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More resources
Google Cloud DatastoreJSqlDbMicrosoft Azure Table StorageOrientDBSpark SQL
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