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DBMS > Citus vs. Google Cloud Datastore vs. Kdb vs. Tibero

System Properties Comparison Citus vs. Google Cloud Datastore vs. Kdb vs. Tibero

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKdb  Xexclude from comparisonTibero  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHigh performance Time Series DBMSA secure RDBMS, designed for easy portability from Oracle
Primary database modelRelational DBMSDocument storeTime Series DBMS
Vector DBMS
Relational DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#123  Overall
#60  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score7.70
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score1.81
Rank#143  Overall
#65  Relational DBMS
Websitewww.citusdata.comcloud.google.com/­datastorekx.comus.tmaxsoft.com/­products/­tibero
Technical documentationdocs.citusdata.comcloud.google.com/­datastore/­docscode.kx.comtechnet.tmaxsoft.com/­upload/­download/­online/­tibero/­pver-20150504-000002/­index.html
DeveloperGoogleKx Systems, a division of First Derivatives plcTmaxSoft
Initial release201020082000 infokdb was released 2000, kdb+ in 20032003
Current release8.1, December 20183.6, May 20186, April 2015
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercial infofree 32-bit versioncommercial
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 languageCqC and Assembler
Server operating systemsLinuxhostedLinux
OS X
Solaris
Windows
AIX
HP-UX
Linux
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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 functionalitynoyesyes
Secondary indexesyesyesyes infotable attribute 'grouped'yes
SQL infoSupport of SQLyes infostandard, with numerous extensionsSQL-like query language (GQL)SQL-like query language (q)yes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.using Google App Engineuser defined functionsPersistent Stored Procedure (PSM)
TriggersyesCallbacks using the Google Apps Engineyes infowith viewsyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioninghorizontal partitioning infoby range, hash, list or composite
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication using PaxosSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno infosimilar paradigm used for internal processingno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
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.nonoyesno infoplanned for next version
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)rights management via user accountsfine grained access rights according to SQL-standard (SQL 92, SQL 99)
More information provided by the system vendor
CitusGoogle Cloud DatastoreKdbTibero
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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CitusGoogle Cloud DatastoreKdbTibero
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