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DBMS > Google Cloud Datastore vs. Microsoft Azure Table Storage vs. MonetDB vs. TimesTen

System Properties Comparison Google Cloud Datastore vs. Microsoft Azure Table Storage vs. MonetDB vs. TimesTen

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonMonetDB  Xexclude from comparisonTimesTen  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 datasetsA relational database management system that stores data in columnsIn-Memory RDBMS compatible to Oracle
Primary database modelDocument storeWide column storeRelational DBMSRelational 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
Score4.04
Rank#77  Overall
#6  Wide column stores
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score1.36
Rank#161  Overall
#75  Relational DBMS
Websitecloud.google.com/­datastoreazure.microsoft.com/­en-us/­services/­storage/­tableswww.monetdb.orgwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationcloud.google.com/­datastore/­docswww.monetdb.org/­Documentationdocs.oracle.com/­database/­timesten-18.1
DeveloperGoogleMicrosoftMonetDB BVOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2008201220041998
Current releaseDec2023 (11.49), December 202311 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMozilla Public License 2.0commercial
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
Server operating systemshostedhostedFreeBSD
Linux
OS X
Solaris
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-freeschema-freeyesyes
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.nonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query language (GQL)noyes infoSQL 2003 with some extensionsyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIJDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresusing Google App Enginenoyes, in SQL, C, RPL/SQL
TriggersCallbacks using the Google Apps Enginenoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding via remote tablesnone
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.none infoSource-replica replication available in experimental statusMulti-source replication
Source-replica replication
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 Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesyes
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 infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
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 signaturesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreMicrosoft Azure Table StorageMonetDBTimesTen
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