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DBMS > AllegroGraph vs. Graph Engine vs. HBase vs. Spark SQL

System Properties Comparison AllegroGraph vs. Graph Engine vs. HBase vs. Spark SQL

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHBase  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineWide-column store based on Apache Hadoop and on concepts of BigTableSpark 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
Graph DBMS
Key-value store
Wide column storeRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.06
Rank#187  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteallegrograph.comwww.graphengine.iohbase.apache.orgspark.apache.org/­sql
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlwww.graphengine.io/­docs/­manualhbase.apache.org/­book.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFranz Inc.MicrosoftApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation
Initial release2004201020082014
Current release8.0, December 20232.3.4, January 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoMIT LicenseOpen Source infoApache version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation language.NET and CJavaScala
Server operating systemsLinux
OS X
Windows
.NETLinux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
Data schemeyes infoRDF schemasyesschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes
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 possiblenonono
Secondary indexesyesnono
SQL infoSupport of SQLSPARQL is used as query languagenonoSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP API
SPARQL
RESTful HTTP APIJava API
RESTful HTTP API
Thrift
JDBC
ODBC
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
C#
C++
F#
Visual Basic
C
C#
C++
Groovy
Java
PHP
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispyesyes infoCoprocessors in Javano
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodeswith Federationhorizontal partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoSingle row ACID (across millions of columns)no
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesoptional: 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 controlUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACno
More information provided by the system vendor
AllegroGraphGraph Engine infoformer name: TrinityHBaseSpark 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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