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DBMS > PlanetScale vs. Postgres-XL vs. PostgreSQL vs. Splice Machine vs. Yanza

System Properties Comparison PlanetScale vs. Postgres-XL vs. PostgreSQL vs. Splice Machine vs. Yanza

Editorial information provided by DB-Engines
NamePlanetScale  Xexclude from comparisonPostgres-XL  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSplice Machine  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionScalable, distributed, serverless MySQL database platform built on top of VitessBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkTime Series DBMS for IoT Applications
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.Relational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store
Spatial DBMS
Document 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
Score1.49
Rank#155  Overall
#72  Relational DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteplanetscale.comwww.postgres-xl.orgwww.postgresql.orgsplicemachine.comyanza.com
Technical documentationplanetscale.com/­docswww.postgres-xl.org/­documentationwww.postgresql.org/­docssplicemachine.com/­how-it-works
DeveloperPlanetScalePostgreSQL Global Development Group infowww.postgresql.org/­developerSplice MachineYanza
Initial release20202014 infosince 2012, originally named StormDB1989 info1989: Postgres, 1996: PostgreSQL20142015
Current release10 R1, October 201816.3, May 20243.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoMozilla public licenseOpen Source infoBSDOpen Source infoAGPL 3.0, commercial license availablecommercial infofree version available
Cloud-based only infoOnly available as a cloud serviceyesnononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoCCJava
Server operating systemsDocker
Linux
macOS
Linux
macOS
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
OS X
Solaris
Windows
Windows
Data schemeyesyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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.yes infoXML type, but no XML query functionalityyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLyes infowith proprietary extensionsyes infodistributed, parallel query executionyes infostandard with numerous extensionsyesno
APIs and other access methodsADO.NET
JDBC
MySQL protocol
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
Native Spark Datasource
ODBC
HTTP API
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresyes infoproprietary syntaxuser defined functionsuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infoJavano
Triggersyesyesyesyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningpartitioning by range, list and (since PostgreSQL 11) by hashShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency across shards
Immediate Consistency within a shard
Immediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infonot for MyISAM storage engineyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at shard levelACID infoMVCCACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayes infotable locks or row locks depending on storage engineyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlUsers with fine-grained authorization concept infono user groups or rolesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardno

More information provided by the system vendor

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More resources
PlanetScalePostgres-XLPostgreSQLSplice MachineYanza
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