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DBMS > Citus vs. Coveo vs. DolphinDB

System Properties Comparison Citus vs. Coveo vs. DolphinDB

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonCoveo  Xexclude from comparisonDolphinDB  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentDolphinDB 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.
Primary database modelRelational DBMSSearch engineTime Series DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score2.28
Rank#114  Overall
#11  Search engines
Score4.13
Rank#80  Overall
#6  Time Series DBMS
Websitewww.citusdata.comwww.coveo.comwww.dolphindb.com
Technical documentationdocs.citusdata.comdocs.coveo.comdocs.dolphindb.cn/­en/­help200/­index.html
DeveloperCoveoDolphinDB, Inc
Initial release201020122018
Current release8.1, December 2018v2.00.4, January 2022
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercial infofree community version available
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++
Server operating systemsLinuxhostedLinux
Windows
Data schemeyeshybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationyes
Typing infopredefined data types such as float or dateyesyesyes
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
Secondary indexesyesyesyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoSQL-like query language
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP APIJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
Java
JavaScript
Python
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyes
Triggersyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyeshorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesyes
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlfine grained access rights according to SQL-standardgranular access controls, API key management, content filtersAdministrators, Users, Groups

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More resources
CitusCoveoDolphinDB
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