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DBMS > AllegroGraph vs. Kinetica vs. LeanXcale vs. STSdb

System Properties Comparison AllegroGraph vs. Kinetica vs. LeanXcale vs. STSdb

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonKinetica  Xexclude from comparisonLeanXcale  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSGPU-accelerated database for real-time analysis of large and streaming datasetsA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Relational DBMSKey-value store
Relational DBMS
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.04
Rank#165  Overall
#26  Document stores
#14  Graph DBMS
#7  RDF stores
Score0.80
Rank#190  Overall
#94  Relational DBMS
Score0.29
Rank#265  Overall
#44  Key-value stores
#122  Relational DBMS
Score0.08
Rank#310  Overall
#51  Key-value stores
Websiteallegrograph.comwww.kinetica.comwww.leanxcale.comgithub.com/­STSSoft/­STSdb4
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlwww.kinetica.com/­docs
DeveloperFranz Inc.KineticaLeanXcaleSTS Soft SC
Initial release2004201220152011
Current release7.0.0, April 20206.04.0.8, September 2015
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialcommercialOpen Source infoGPLv2, commercial license available
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 languageC, C++C#
Server operating systemsLinux
OS X
Windows
LinuxWindows
Data schemeyes infoRDF schemasyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infoprimitive types and user defined types (classes)
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 possibleno
Secondary indexesyesyesno
SQL infoSupport of SQLSPARQL is used as query languageSQL-like DML and DDL statementsyes infothrough Apache Derbyno
APIs and other access methodsRESTful HTTP API
SPARQL
JDBC
ODBC
RESTful HTTP API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
.NET Client API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
C
Java
Scala
C#
Java
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispuser defined functionsno
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
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.noyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess rights for users and roles on table levelno
More information provided by the system vendor
AllegroGraphKineticaLeanXcaleSTSdb
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Full ACID and full SQL operational database with analytical queries over operational...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
Linear scalability upto 100s of nodes (tested with 100 nodes and TPC-C).
» more
Typical application scenariosHybrid Transactional-Analytical Processing (HTAP) requiring an operational database...
» more
Key customersbanking/finance/fintech, telco, insurance, traveltech, M2M/IoT, retail
» more
Market metrics15 beta testers
» more
Licensing and pricing modelsannual fee covering license and support based on number of physical cores
» more
News

Data Fabrics and Knowledge Graphs — A Symbiotic Relationship
6 November 2020

RDF vs Property Graph – The Graph Show
3 November 2020

Text Analytics Forum 2020 – KMWorld Connect
27 October 2020

Sharing Ontologies Globally To Speed Science And Healthcare Solutions – OntoPortal
7 October 2020

Knowledge Graphs: A Single Source of Truth for the Enterprise
5 October 2020

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
AllegroGraphKineticaLeanXcaleSTSdb
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