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DBMS > Google Cloud Datastore vs. Microsoft Access vs. PostgreSQL

System Properties Comparison Google Cloud Datastore vs. Microsoft Access vs. PostgreSQL

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonPostgreSQL  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.)Widely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelDocument storeRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.62
Rank#71  Overall
#12  Document stores
Score95.91
Rank#13  Overall
#9  Relational DBMS
Score674.32
Rank#4  Overall
#4  Relational DBMS
Websitecloud.google.com/­datastorewww.microsoft.com/­en-us/­microsoft-365/­accesswww.postgresql.org
Technical documentationcloud.google.com/­datastore/­docsdeveloper.microsoft.com/­en-us/­accesswww.postgresql.org/­docs
DeveloperGoogleMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release200819921989 info1989: Postgres, 1996: PostgreSQL
Current release1902 (16.0.11328.20222), March 201916.4, August 2024
License infoCommercial or Open Sourcecommercialcommercial infoBundled with Microsoft OfficeOpen Source infoBSD
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
PostgreSQL Flex @ STACKIT offers managed PostgreSQL Instances with adjustable CPU, RAM, storage amount and speed and several extensions available, in enterprise grade to perfectly match all application requirements. All 100% GDPR-compliant.
Implementation languageC++C
Server operating systemshostedWindows infoNot a real database server, but making use of DLLsFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeschema-freeyesyes
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.noyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)yes infobut not compliant to any SQL standardyes infostandard with numerous extensions
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DAO
ODBC
OLE DB
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
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresusing Google App Engineyes infosince Access 2010 using the ACE-engineuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
TriggersCallbacks using the Google Apps Engineyes infosince Access 2010 using the ACE-engineyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonepartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosnoneSource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownono
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 pathsyesyes
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
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
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 2003fine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreMicrosoft AccessPostgreSQL
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