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DBMS > Google BigQuery vs. Google Cloud Spanner vs. PostgreSQL

System Properties Comparison Google BigQuery vs. Google Cloud Spanner vs. PostgreSQL

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Widely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelRelational DBMSRelational 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
Score62.88
Rank#19  Overall
#13  Relational DBMS
Score2.56
Rank#97  Overall
#50  Relational DBMS
Score674.32
Rank#4  Overall
#4  Relational DBMS
Websitecloud.google.com/­bigquerycloud.google.com/­spannerwww.postgresql.org
Technical documentationcloud.google.com/­bigquery/­docscloud.google.com/­spanner/­docswww.postgresql.org/­docs
DeveloperGoogleGooglePostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release201020171989 info1989: Postgres, 1996: PostgreSQL
Current release16.4, August 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud serviceyesyesno
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
Server operating systemshostedhostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nonoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesnoyesyes
SQL infoSupport of SQLyesyes infoQuery statements complying to ANSI 2011yes infostandard with numerous extensions
APIs and other access methodsRESTful HTTP/JSON APIgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingpartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.Source-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataACID infoStrict serializable isolationACID
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.nonono
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Google BigQueryGoogle Cloud SpannerPostgreSQL
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