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DBMS > OrigoDB vs. Postgres-XL vs. Spark SQL

System Properties Comparison OrigoDB vs. Postgres-XL vs. Spark SQL

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Editorial information provided by DB-Engines
NameOrigoDB  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA fully ACID in-memory object graph databaseBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Object oriented DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteorigodb.comwww.postgres-xl.orgspark.apache.org/­sql
Technical documentationorigodb.com/­docswww.postgres-xl.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperRobert Friberg et alApache Software Foundation
Initial release2009 infounder the name LiveDB2014 infosince 2012, originally named StormDB2014
Current release10 R1, October 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen SourceOpen Source infoMozilla public licenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#CScala
Server operating systemsLinux
Windows
Linux
macOS
Linux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateUser defined using .NET types and collectionsyesyes
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.no infocan be achieved using .NETyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesno
SQL infoSupport of SQLnoyes infodistributed, parallel query executionSQL-like DML and DDL statements
APIs and other access methods.NET Client API
HTTP API
LINQ
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languages.Net.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesuser defined functionsno
Triggersyes infoDomain Eventsyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoclient side managed; servers are not synchronizedhorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritydepending on modelyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoMVCCno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infoWrite ahead logyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlRole based authorizationfine grained access rights according to SQL-standardno

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More resources
OrigoDBPostgres-XLSpark SQL
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