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DBMS > Citus vs. Dragonfly vs. Microsoft Azure Data Explorer vs. MonetDB vs. TimesTen

System Properties Comparison Citus vs. Dragonfly vs. Microsoft Azure Data Explorer vs. MonetDB vs. TimesTen

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonDragonfly  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMonetDB  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceFully managed big data interactive analytics platformA relational database management system that stores data in columnsIn-Memory RDBMS compatible to Oracle
Primary database modelRelational DBMSKey-value storeRelational DBMS infocolumn orientedRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score0.41
Rank#266  Overall
#38  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.72
Rank#145  Overall
#67  Relational DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitewww.citusdata.comgithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
azure.microsoft.com/­services/­data-explorerwww.monetdb.orgwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.citusdata.comwww.dragonflydb.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.monetdb.org/­Documentationdocs.oracle.com/­database/­timesten-18.1
DeveloperDragonflyDB team and community contributorsMicrosoftMonetDB BVOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20102023201920041998
Current release8.1, December 20181.0, March 2023cloud service with continuous releasesDec2023 (11.49), December 202311 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoBSL 1.1commercialOpen Source infoMozilla Public License 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++C
Server operating systemsLinuxLinuxhostedFreeBSD
Linux
OS X
Solaris
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesscheme-freeFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyesstrings, hashes, lists, sets, sorted sets, bit arraysyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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 functionalitynoyesno
Secondary indexesyesnoall fields are automatically indexedyesyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoKusto Query Language (KQL), SQL subsetyes infoSQL 2003 with some extensionsyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocol infoRESP - REdis Serialization ProtocolMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.LuaYes, possible languages: KQL, Python, Ryes, in SQL, C, RPL/SQL
Triggersyespublish/subscribe channels provide some trigger functionalityyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding via remote tablesnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none infoSource-replica replication available in experimental statusMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of command blocks and scriptsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardPassword-based authenticationAzure Active Directory Authenticationfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
CitusDragonflyMicrosoft Azure Data ExplorerMonetDBTimesTen
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