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DBMS > Google Cloud Datastore vs. Microsoft Azure Table Storage vs. ObjectBox vs. OpenQM

System Properties Comparison Google Cloud Datastore vs. Microsoft Azure Table Storage vs. ObjectBox vs. OpenQM

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonObjectBox  Xexclude from comparisonOpenQM infoalso called QM  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA Wide Column Store for rapid development using massive semi-structured datasetsExtremely fast embedded database for small devices, IoT and MobileQpenQM is a high-performance, self-tuning, multi-value DBMS
Primary database modelDocument storeWide column storeObject oriented DBMSMultivalue DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Score0.34
Rank#284  Overall
#10  Multivalue DBMS
Websitecloud.google.com/­datastoreazure.microsoft.com/­en-us/­services/­storage/­tablesobjectbox.iowww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qm
Technical documentationcloud.google.com/­datastore/­docsdocs.objectbox.io
DeveloperGoogleMicrosoftObjectBox LimitedRocket Software, originally Martin Phillips
Initial release2008201220171993
Current release3.4-12
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache License 2.0Open Source infoGPLv2, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++
Server operating systemshostedhostedAndroid
iOS
Linux
macOS
Windows
AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
Data schemeschema-freeschema-freeyesyes infowith some exceptions
Typing infopredefined data types such as float or dateyes, details hereyesyes
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
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query language (GQL)nonono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIProprietary native API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
.Net
Basic
C
Java
Objective C
PHP
Python
Server-side scripts infoStored proceduresusing Google App Enginenonoyes
TriggersCallbacks using the Google Apps Enginenonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenoneyes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.online/offline synchronization between client and serveryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsoptimistic lockingACIDACID
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.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 signaturesyesAccess rights can be defined down to the item level
More information provided by the system vendor
Google Cloud DatastoreMicrosoft Azure Table StorageObjectBoxOpenQM infoalso called QM
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More resources
Google Cloud DatastoreMicrosoft Azure Table StorageObjectBoxOpenQM infoalso called QM
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