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DBMS > AllegroGraph vs. Amazon DocumentDB vs. Kinetica vs. Netezza

System Properties Comparison AllegroGraph vs. Amazon DocumentDB vs. Kinetica vs. Netezza

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Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonAmazon DocumentDB  Xexclude from comparisonKinetica  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSFast, scalable, highly available, and fully managed MongoDB-compatible database serviceFully vectorized database across both GPUs and CPUsData warehouse and analytics appliance part of IBM PureSystems
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Document storeRelational DBMSRelational 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
Score1.91
Rank#124  Overall
#22  Document stores
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score7.56
Rank#48  Overall
#31  Relational DBMS
Websiteallegrograph.comaws.amazon.com/­documentdbwww.kinetica.comwww.ibm.com/­products/­netezza
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlaws.amazon.com/­documentdb/­resourcesdocs.kinetica.com
DeveloperFranz Inc.KineticaIBM
Initial release2004201920122000
Current release8.0, December 20237.1, August 2021
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++
Server operating systemsLinux
OS X
Windows
hostedLinuxLinux infoincluded in appliance
Data schemeyes infoRDF schemasschema-freeyesyes
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 possiblenono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSPARQL is used as query languagenoSQL-like DML and DDL statementsyes
APIs and other access methodsRESTful HTTP API
SPARQL
proprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
OLE DB
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
Go
Java
JavaScript (Node.js)
PHP
Python
C++
Java
JavaScript (Node.js)
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispnouser defined functionsyes
Triggersyesnoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodeswith FederationnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-availability zones for high availability, asynchronous replication for up to 15 read replicasSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynono infotypically not used, however similar functionality with DBRef possibleyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-document operationsnoACID
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 RAM
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess rights for users and rolesAccess rights for users and roles on table levelUsers with fine-grained authorization concept
More information provided by the system vendor
AllegroGraphAmazon DocumentDBKineticaNetezza infoAlso called PureData System for Analytics by IBM
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
AllegroGraphAmazon DocumentDBKineticaNetezza infoAlso called PureData System for Analytics by IBM
Recent citations in the news

Build your own chatbot and talk to your own documents
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11 December 2023, Datanami

Fuse Graph Neural Networks with Semantic Reasoning to Produce Complimentary Predictions
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16 May 2024, AWS Blog

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15 April 2024, AWS Blog

Update your Amazon DocumentDB TLS certificates: Expiring in 2024
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Kinetica: AI is a ‘killer app’ for data analytics
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Unify and share data across Netezza and watsonx.data for new generative AI applications
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21 August 2019, AWS Blog

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Copy data from Netezza to Azure with Azure Data Factory
9 September 2019, Microsoft

IBM Completes Acquisition of Netezza
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