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DBMS > Google Cloud Datastore vs. PostgreSQL vs. RDF4J vs. Yaacomo

System Properties Comparison Google Cloud Datastore vs. PostgreSQL vs. RDF4J vs. Yaacomo

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonPostgreSQL  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument storeRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.RDF storeRelational DBMS
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
Score4.36
Rank#72  Overall
#12  Document stores
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websitecloud.google.com/­datastorewww.postgresql.orgrdf4j.orgyaacomo.com
Technical documentationcloud.google.com/­datastore/­docswww.postgresql.org/­docsrdf4j.org/­documentation
DeveloperGooglePostgreSQL Global Development Group infowww.postgresql.org/­developerSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Q2WEB GmbH
Initial release20081989 info1989: Postgres, 1996: PostgreSQL20042009
Current release16.3, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoBSDOpen Source infoEclipse Distribution License (EDL), v1.0.commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJava
Server operating systemshostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
OS X
Unix
Windows
Android
Linux
Windows
Data schemeschema-freeyesyes infoRDF Schemasyes
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 infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)yes infostandard with numerous extensionsnoyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
PHP
Python
Server-side scripts infoStored proceduresusing Google App Engineuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes
TriggersCallbacks using the Google Apps Engineyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and (since PostgreSQL 11) by hashnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replication infoother methods possible by using 3rd party extensionsnoneSource-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
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 TransactionsACIDACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes
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)fine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
Google Cloud DatastorePostgreSQLRDF4J infoformerly known as SesameYaacomo
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