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DBMS > Google Cloud Datastore vs. Microsoft Access vs. PlanetScale vs. Postgres-XL

System Properties Comparison Google Cloud Datastore vs. Microsoft Access vs. PlanetScale vs. Postgres-XL

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonPlanetScale  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Scalable, distributed, serverless MySQL database platform built on top of VitessBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelDocument storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score1.59
Rank#151  Overall
#70  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websitecloud.google.com/­datastorewww.microsoft.com/­en-us/­microsoft-365/­accessplanetscale.comwww.postgres-xl.org
Technical documentationcloud.google.com/­datastore/­docsdeveloper.microsoft.com/­en-us/­accessplanetscale.com/­docswww.postgres-xl.org/­documentation
DeveloperGoogleMicrosoftPlanetScale
Initial release2008199220202014 infosince 2012, originally named StormDB
Current release1902 (16.0.11328.20222), March 201910 R1, October 2018
License infoCommercial or Open Sourcecommercialcommercial infoBundled with Microsoft OfficecommercialOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoC
Server operating systemshostedWindows infoNot a real database server, but making use of DLLsDocker
Linux
macOS
Linux
macOS
Data schemeschema-freeyesyesyes
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.noyes infoXML type, but no XML query functionality
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)yes infobut not compliant to any SQL standardyes infowith proprietary extensionsyes infodistributed, parallel query execution
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DAO
ODBC
OLE DB
ADO.NET
JDBC
MySQL protocol
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresusing Google App Engineyes infosince Access 2010 using the ACE-engineyes infoproprietary syntaxuser defined functions
TriggersCallbacks using the Google Apps Engineyes infosince Access 2010 using the ACE-engineyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosnoneMulti-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.Eventual Consistency across shards
Immediate Consistency within a shard
Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesyes infonot for MyISAM storage engineyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infobut no files for transaction loggingACID at shard levelACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyes
Durability infoSupport for making data persistentyesyes infobut no files for transaction loggingyesyes
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)no infoa simple user-level security was built in till version Access 2003Users with fine-grained authorization concept infono user groups or rolesfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreMicrosoft AccessPlanetScalePostgres-XL
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