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DBMS > Citus vs. DolphinDB vs. Oracle Rdb vs. Spark SQL vs. WakandaDB

System Properties Comparison Citus vs. DolphinDB vs. Oracle Rdb vs. Spark SQL vs. WakandaDB

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonDolphinDB  Xexclude from comparisonOracle Rdb  Xexclude from comparisonSpark SQL  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.Spark SQL is a component on top of 'Spark Core' for structured data processingWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMSObject oriented DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score4.03
Rank#78  Overall
#6  Time Series DBMS
Score1.14
Rank#178  Overall
#80  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websitewww.citusdata.comwww.dolphindb.comwww.oracle.com/­database/­technologies/­related/­rdb.htmlspark.apache.org/­sqlwakanda.github.io
Technical documentationdocs.citusdata.comdocs.dolphindb.cn/­en/­help200/­index.htmlwww.oracle.com/­database/­technologies/­related/­rdb-doc.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwakanda.github.io/­doc
DeveloperDolphinDB, IncOracle, originally developed by Digital Equipment Corporation (DEC)Apache Software FoundationWakanda SAS
Initial release20102018198420142012
Current release8.1, December 2018v2.00.4, January 20227.4.1.1, 20213.5.0 ( 2.13), September 20232.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercial infofree community version availablecommercialOpen Source infoApache 2.0Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++ScalaC++, JavaScript
Server operating systemsLinuxLinux
Windows
HP Open VMSLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 functionalitynononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyes infostandard, with numerous extensionsSQL-like query languageyesSQL-like DML and DDL statementsno
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
Java
Python
R
Scala
JavaScript
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yesnoyes
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesyes, on a single nodenoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.noyesnonono
User concepts infoAccess controlfine grained access rights according to SQL-standardAdministrators, Users, Groupsnoyes

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More resources
CitusDolphinDBOracle RdbSpark SQLWakandaDB
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