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DBMS > Google Cloud Datastore vs. Ingres vs. ObjectBox vs. PostgreSQL

System Properties Comparison Google Cloud Datastore vs. Ingres vs. ObjectBox vs. PostgreSQL

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonIngres  Xexclude from comparisonObjectBox  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWell established RDBMSExtremely fast embedded database for small devices, IoT and MobileWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelDocument storeRelational DBMSObject oriented DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsTime Series DBMSDocument 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
Score4.47
Rank#76  Overall
#12  Document stores
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Websitecloud.google.com/­datastorewww.actian.com/­databases/­ingresobjectbox.iowww.postgresql.org
Technical documentationcloud.google.com/­datastore/­docsdocs.actian.com/­ingresdocs.objectbox.iowww.postgresql.org/­docs
DeveloperGoogleActian CorporationObjectBox LimitedPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release20081974 infooriginally developed at University Berkely in early 1970s20171989 info1989: Postgres, 1996: PostgreSQL
Current release11.2, May 202216.3, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache License 2.0Open Source infoBSD
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC and C++C
Server operating systemshostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Android
iOS
Linux
macOS
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
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.nono infobut tools for importing/exporting data from/to XML-files availablenoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)yesnoyes infostandard with numerous extensions
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Proprietary native APIADO.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++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresusing Google App Engineyesnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
TriggersCallbacks using the Google Apps Engineyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslynonepartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosIngres Replicatoronline/offline synchronization between client and serverSource-replica replication infoother methods possible by using 3rd party extensions
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 pathsyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyes
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.nononono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardyesfine grained access rights according to SQL-standard
More information provided by the system vendor
Google Cloud DatastoreIngresObjectBoxPostgreSQL
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