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DBMS > Citus vs. Dragonfly vs. Graph Engine vs. Microsoft Azure Synapse Analytics vs. Spark SQL

System Properties Comparison Citus vs. Dragonfly vs. Graph Engine vs. Microsoft Azure Synapse Analytics vs. Spark SQL

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonDragonfly  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSpark SQL  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 instanceA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value storeGraph DBMS
Key-value store
Relational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score0.49
Rank#261  Overall
#38  Key-value stores
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.citusdata.comgithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.graphengine.ioazure.microsoft.com/­services/­synapse-analyticsspark.apache.org/­sql
Technical documentationdocs.citusdata.comwww.dragonflydb.io/­docswww.graphengine.io/­docs/­manualdocs.microsoft.com/­azure/­synapse-analyticsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDragonflyDB team and community contributorsMicrosoftMicrosoftApache Software Foundation
Initial release20102023201020162014
Current release8.1, December 20181.0, March 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoBSL 1.1Open Source infoMIT LicensecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++.NET and CC++Scala
Server operating systemsLinuxLinux.NEThostedLinux
OS X
Windows
Data schemeyesscheme-freeyesyesyes
Typing infopredefined data types such as float or dateyesstrings, hashes, lists, sets, sorted sets, bit arraysyesyesyes
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 indexesyesnoyesno
SQL infoSupport of SQLyes infostandard, with numerous extensionsnonoyesSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocol infoRESP - REdis Serialization ProtocolRESTful HTTP APIADO.NET
JDBC
ODBC
JDBC
ODBC
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
C#
C++
F#
Visual Basic
C#
Java
PHP
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.LuayesTransact SQLno
Triggersyespublish/subscribe channels provide some trigger functionalitynonono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding, horizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of command blocks and scriptsnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardPassword-based authenticationyesno

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More resources
CitusDragonflyGraph Engine infoformer name: TrinityMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSpark SQL
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