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DBMS > AllegroGraph vs. Citus vs. PlanetScale vs. Spark SQL

System Properties Comparison AllegroGraph vs. Citus vs. PlanetScale vs. Spark SQL

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonCitus  Xexclude from comparisonPlanetScale  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLScalable, distributed, serverless MySQL database platform built on top of VitessSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.13
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score1.49
Rank#155  Overall
#72  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteallegrograph.comwww.citusdata.complanetscale.comspark.apache.org/­sql
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.citusdata.complanetscale.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFranz Inc.PlanetScaleApache Software Foundation
Initial release2004201020202014
Current release8.0, December 20238.1, December 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCGoScala
Server operating systemsLinux
OS X
Windows
LinuxDocker
Linux
macOS
Linux
OS X
Windows
Data schemeyes infoRDF schemasyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.no infobulk load of XML files possibleyes infospecific XML type available, but no XML query functionalityno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSPARQL is used as query languageyes infostandard, with numerous extensionsyes infowith proprietary extensionsSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP API
SPARQL
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
MySQL protocol
ODBC
JDBC
ODBC
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infoproprietary syntaxno
Triggersyesyesyesno
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesyes infonot for MyISAM storage engineno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID at shard levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyes
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
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationfine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or rolesno
More information provided by the system vendor
AllegroGraphCitusPlanetScaleSpark SQL
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
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