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DBMS > Google Cloud Spanner vs. Kinetica vs. MonetDB vs. Postgres-XL

System Properties Comparison Google Cloud Spanner vs. Kinetica vs. MonetDB vs. Postgres-XL

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Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonKinetica  Xexclude from comparisonMonetDB  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionA 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.Fully vectorized database across both GPUs and CPUsA relational database management system that stores data in columnsBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score1.72
Rank#145  Overall
#67  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websitecloud.google.com/­spannerwww.kinetica.comwww.monetdb.orgwww.postgres-xl.org
Technical documentationcloud.google.com/­spanner/­docsdocs.kinetica.comwww.monetdb.org/­Documentationwww.postgres-xl.org/­documentation
DeveloperGoogleKineticaMonetDB BV
Initial release2017201220042014 infosince 2012, originally named StormDB
Current release7.1, August 2021Dec2023 (11.49), December 202310 R1, October 2018
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMozilla Public License 2.0Open Source infoMozilla public license
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++CC
Server operating systemshostedLinuxFreeBSD
Linux
OS X
Solaris
Windows
Linux
macOS
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 infoXML type, but no XML query functionality
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011SQL-like DML and DDL statementsyes infoSQL 2003 with some extensionsyes infodistributed, parallel query execution
APIs and other access methodsgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnouser defined functionsyes, in SQL, C, Ruser defined functions
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding via remote tableshorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.Source-replica replicationnone infoSource-replica replication available in experimental status
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationnoACIDACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Google Cloud SpannerKineticaMonetDBPostgres-XL
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