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DBMS > AllegroGraph vs. GridDB vs. InterSystems Caché vs. Microsoft Azure Data Explorer vs. OrientDB

System Properties Comparison AllegroGraph vs. GridDB vs. InterSystems Caché vs. Microsoft Azure Data Explorer vs. OrientDB

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonGridDB  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOrientDB  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSScalable in-memory time series database optimized for IoT and Big DataA multi-model DBMS and application serverFully managed big data interactive analytics platformMulti-model DBMS (Document, Graph, Key/Value)
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Time Series DBMSKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMS infocolumn orientedDocument store
Graph DBMS
Key-value store
Secondary database modelsSpatial DBMSKey-value store
Relational DBMS
Document storeDocument 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
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score3.19
Rank#93  Overall
#16  Document stores
#7  Graph DBMS
#14  Key-value stores
Websiteallegrograph.comgriddb.netwww.intersystems.com/­products/­cacheazure.microsoft.com/­services/­data-explorerorientdb.org
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.griddb.netdocs.intersystems.comdocs.microsoft.com/­en-us/­azure/­data-explorerwww.orientdb.com/­docs/­last/­index.html
DeveloperFranz Inc.Toshiba CorporationInterSystemsMicrosoftOrientDB LTD; CallidusCloud; SAP
Initial release20042013199720192010
Current release8.0, December 20235.1, August 20222018.1.4, May 2020cloud service with continuous releases3.2.29, March 2024
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialcommercialOpen Source infoApache version 2
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemsLinux
OS X
Windows
LinuxAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
hostedAll OS with a Java JDK (>= JDK 6)
Data schemeyes infoRDF schemasyesdepending on used data modelFixed schema with schema-less datatypes (dynamic)schema-free infoSchema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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 possiblenoyesyesno
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSPARQL is used as query languageSQL92, SQL-like TQL (Toshiba Query Language)yesKusto Query Language (KQL), SQL subsetSQL-like query language, no joins
APIs and other access methodsRESTful HTTP API
SPARQL
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infoJavaScript or Common LispnoyesYes, possible languages: KQL, Python, RJava, Javascript
Triggersyesyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyHooks
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingnoneSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno infocould be achieved with distributed queries
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate consistency within container, eventual consistency across containersImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnoyes inforelationship in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACIDnoACID
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.noyesyesno
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess rights for users can be defined per databaseAccess rights for users, groups and rolesAzure Active Directory AuthenticationAccess rights for users and roles; record level security configurable
More information provided by the system vendor
AllegroGraphGridDBInterSystems CachéMicrosoft Azure Data ExplorerOrientDB
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
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