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DBMS > AllegroGraph vs. HEAVY.AI vs. jBASE vs. Kinetica vs. Microsoft Azure Data Explorer

System Properties Comparison AllegroGraph vs. HEAVY.AI vs. jBASE vs. Kinetica vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonjBASE  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA robust multi-value DBMS comprising development tools and middlewareFully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platform
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMSMultivalue DBMSRelational DBMSRelational DBMS infocolumn oriented
Secondary database modelsSpatial DBMSSpatial DBMSSpatial DBMS
Time Series DBMS
Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
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
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score1.41
Rank#159  Overall
#3  Multivalue DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteallegrograph.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasewww.kinetica.comazure.microsoft.com/­services/­data-explorer
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.heavy.aidocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperFranz Inc.HEAVY.AI, Inc.Rocket Software (formerly Zumasys)KineticaMicrosoft
Initial release20042016199120122019
Current release8.0, December 20235.10, January 20225.77.1, August 2021cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoApache Version 2; enterprise edition availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDAC, C++
Server operating systemsLinux
OS X
Windows
LinuxAIX
Linux
Windows
Linuxhosted
Data schemeyes infoRDF schemasyesschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesoptionalyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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 possiblenoyesnoyes
Secondary indexesyesnoyesall fields are automatically indexed
SQL infoSupport of SQLSPARQL is used as query languageyesEmbedded SQL for jBASE in BASICSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subset
APIs and other access methodsRESTful HTTP API
SPARQL
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Basic
Jabbascript
Java
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispnoyesuser defined functionsYes, possible languages: KQL, Python, R
Triggersyesnoyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeswith FederationSharding infoRound robinShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replicationyesSource-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 methodsnonononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationfine grained access rights according to SQL-standardAccess rights can be defined down to the item levelAccess rights for users and roles on table levelAzure Active Directory Authentication
More information provided by the system vendor
AllegroGraphHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022jBASEKineticaMicrosoft Azure Data Explorer
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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Allegro CL v11 – Now Available! – The Neuro-Symbolic AI Programming Platform
8 January 2024

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More resources
AllegroGraphHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022jBASEKineticaMicrosoft Azure Data Explorer
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