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DBMS > Google Cloud Datastore vs. PostgreSQL vs. Teradata

System Properties Comparison Google Cloud Datastore vs. PostgreSQL vs. Teradata

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonPostgreSQL  Xexclude from comparisonTeradata  Xexclude from comparison
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 SQLA hybrid cloud data analytics software platform (Teradata Vantage)
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.Relational DBMS
Secondary database modelsDocument storeDocument store
Graph DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.81
Rank#67  Overall
#12  Document stores
Score507.19
Rank#4  Overall
#4  Relational DBMS
Score78.29
Rank#15  Overall
#10  Relational DBMS
Websitecloud.google.com/­datastorewww.postgresql.orgwww.teradata.com
Technical documentationcloud.google.com/­datastore/­docswww.postgresql.org/­docs/­manualsdocs.teradata.com
DeveloperGooglePostgreSQL Global Development Group infowww.postgresql.org/­developerTeradata
Initial release20081989 info1989: Postgres, 1996: PostgreSQL1984
Current release12.1, November 2019Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialOpen Source infoBSDcommercial
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.
  • Azure Database for PostgreSQL: A fully managed, scalable PostgreSQL relational database with high availability and security built in at no extra cost
  • ScaleGrid: Fully managed PostgreSQL hosting with high availability, dedicated servers, and superuser control on the #1 multi-cloud Amazon RDS alternative.
Implementation languageC
Server operating systemshostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
hosted
Linux
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.yes
Secondary indexesyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL-like query language (GQL)yes infostandard with numerous extensionsyes infoSQL 2016 + extensions
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
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
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
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
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 infoUDFs, stored procedures, table functions in parallel
TriggersCallbacks using the Google Apps Engineyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and (since PostgreSQL 11) by hashSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-Master replication using PaxosMaster-slave replication infoother methods possible by using 3rd party extensionsMaster-master replication
Master-slave replication
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 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
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
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-standardfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastorePostgreSQLTeradata
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