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DBMS > Citus vs. Google Cloud Bigtable vs. OrigoDB vs. Postgres-XL

System Properties Comparison Citus vs. Google Cloud Bigtable vs. OrigoDB vs. Postgres-XL

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonOrigoDB  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A fully ACID in-memory object graph databaseBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMSKey-value store
Wide column store
Document store
Object oriented DBMS
Relational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Websitewww.citusdata.comcloud.google.com/­bigtableorigodb.comwww.postgres-xl.org
Technical documentationdocs.citusdata.comcloud.google.com/­bigtable/­docsorigodb.com/­docswww.postgres-xl.org/­documentation
DeveloperGoogleRobert Friberg et al
Initial release201020152009 infounder the name LiveDB2014 infosince 2012, originally named StormDB
Current release8.1, December 201810 R1, October 2018
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialOpen SourceOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC#C
Server operating systemsLinuxhostedLinux
Windows
Linux
macOS
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoUser defined using .NET types and collectionsyes
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 infospecific XML type available, but no XML query functionalitynono infocan be achieved using .NETyes infoXML type, but no XML query functionality
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsnonoyes infodistributed, parallel query execution
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
HTTP API
LINQ
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyesuser defined functions
Triggersyesnoyes infoDomain Eventsyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning infoclient side managed; servers are not synchronizedhorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyesnodepending on modelyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role based authorizationfine grained access rights according to SQL-standard

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More resources
CitusGoogle Cloud BigtableOrigoDBPostgres-XL
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