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DBMS > AllegroGraph vs. Heroic vs. Teradata Aster vs. Tkrzw

System Properties Comparison AllegroGraph vs. Heroic vs. Teradata Aster vs. Tkrzw

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonHeroic  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchPlatform for big data analytics on multistructured data sources and typesA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Time Series DBMSRelational DBMSKey-value store
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
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websiteallegrograph.comgithub.com/­spotify/­heroicdbmx.net/­tkrzw
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlspotify.github.io/­heroic
DeveloperFranz Inc.SpotifyTeradataMikio Hirabayashi
Initial release2004201420052020
Current release8.0, December 20230.9.3, August 2020
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoApache 2.0commercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemsLinux
OS X
Windows
LinuxLinux
macOS
Data schemeyes infoRDF schemasschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 possiblenoyes infoin Aster File Storeno
Secondary indexesyesyes infovia Elasticsearchyes
SQL infoSupport of SQLSPARQL is used as query languagenoyesno
APIs and other access methodsRESTful HTTP API
SPARQL
HQL (Heroic Query Language, a JSON-based language)
HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
C
C#
C++
Java
Python
R
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes infoJavaScript or Common LispnoR packagesno
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nononoyes infousing specific database classes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationfine grained access rights according to SQL-standardno
More information provided by the system vendor
AllegroGraphHeroicTeradata AsterTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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
News

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3 April 2024

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9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform
8 January 2024

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More resources
AllegroGraphHeroicTeradata AsterTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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Northwestern University Graduate Students Take on Big Data Using Teradata Aster Discovery Platform in Hackathon
6 May 2015, PR Newswire

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