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DBMS > AllegroGraph vs. Kinetica vs. Microsoft Azure Table Storage vs. NSDb

System Properties Comparison AllegroGraph vs. Kinetica vs. Microsoft Azure Table Storage vs. NSDb

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonNSDb  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSFully vectorized database across both GPUs and CPUsA Wide Column Store for rapid development using massive semi-structured datasetsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMSWide column storeTime Series DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.84
Rank#204  Overall
#35  Document stores
#18  Graph DBMS
#7  RDF stores
#10  Vector DBMS
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score3.55
Rank#80  Overall
#6  Wide column stores
Score0.00
Rank#385  Overall
#40  Time Series DBMS
Websiteallegrograph.comwww.kinetica.comazure.microsoft.com/­en-us/­services/­storage/­tablesnsdb.io
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.kinetica.comnsdb.io/­Architecture
DeveloperFranz Inc.KineticaMicrosoft
Initial release2004201220122017
Current release8.0, December 20237.1, August 2021
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++Java, Scala
Server operating systemsLinux
OS X
Windows
LinuxhostedLinux
macOS
Data schemeyes infoRDF schemasyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes: int, bigint, decimal, string
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 indexesyesyesnoall fields are automatically indexed
SQL infoSupport of SQLSPARQL is used as query languageSQL-like DML and DDL statementsnoSQL-like query language
APIs and other access methodsRESTful HTTP API
SPARQL
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIgRPC
HTTP REST
WebSocket
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Scala
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispuser defined functionsnono
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 FederationShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
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 ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Lucene
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMno
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess rights for users and roles on table levelAccess rights based on private key authentication or shared access signatures
More information provided by the system vendor
AllegroGraphKineticaMicrosoft Azure Table StorageNSDb
News

AllegroGraph Named a 2024 Trend Setting Product
16 September 2024

Gartner recognized Franz Inc. as a Key Neuro-Symbolic AI Provider in 2024 Hype Cycle for AI
10 September 2024

Next-Generation Cybersecurity: Integrating Knowledge Graphs and Neuro-Symbolic AI with STIX and TAXII
10 September 2024

Pruning Cycles in UMLS Metathesaurus: A Neuro Symbolic AI Approach
9 September 2024

Awesome AI Companies – Franz Inc.
17 July 2024

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More resources
AllegroGraphKineticaMicrosoft Azure Table StorageNSDb
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