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DBMS > AllegroGraph vs. AnzoGraph DB vs. Heroic vs. Microsoft Azure Data Explorer vs. Raima Database Manager

System Properties Comparison AllegroGraph vs. AnzoGraph DB vs. Heroic vs. Microsoft Azure Data Explorer vs. Raima Database Manager

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonAnzoGraph DB  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRaima Database Manager infoformerly named db_Vista  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully managed big data interactive analytics platformRDBMS with a small footprint, either embedded into an application or used as a database server
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Graph DBMS
RDF store
Time Series DBMSRelational DBMS infocolumn orientedRelational DBMS
Time Series DBMS
Secondary database modelsSpatial DBMSDocument 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
Score1.13
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.49
Rank#259  Overall
#121  Relational DBMS
#21  Time Series DBMS
Websiteallegrograph.comcambridgesemantics.com/­anzographgithub.com/­spotify/­heroicazure.microsoft.com/­services/­data-explorerraima.com
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.raima.com
DeveloperFranz Inc.Cambridge SemanticsSpotifyMicrosoftRaima Inc.
Initial release20042018201420191984
Current release8.0, December 20232.3, January 2021cloud service with continuous releases15, June 2021
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercial infofree trial version availableOpen Source infoApache 2.0commercialcommercial
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 languageJavaC
Server operating systemsLinux
OS X
Windows
LinuxhostedAndroid
HP-UX
Integrity RTOS
iOS
Linux
OS X
QNX
Solaris
VxWorks
Windows
Data schemeyes infoRDF schemasSchema-free and OWL/RDFS-schema supportschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyes 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 possiblenonoyesno infoExporting/Importing of XML structures possible
Secondary indexesyesnoyes infovia Elasticsearchall fields are automatically indexedyes
SQL infoSupport of SQLSPARQL is used as query languageSPARQL and SPARQL* as primary query language. Cypher preview.noKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsRESTful HTTP API
SPARQL
Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
C++
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Objective-C
PL/SQL
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispuser defined functions and aggregatesnoYes, possible languages: KQL, Python, Ryes infobased on the ANSI/ISO SQL Persistent Stored Modules (PSM) specification
Triggersyesnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodeswith FederationAutomatic shardingShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication in MPP-Clusteryesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoKerberos/HDFS data loadingnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency in MPP-ClusterEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynono infonot needed in graphsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
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.noyesnonoyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess rights for users and rolesAzure Active Directory Authenticationno
More information provided by the system vendor
AllegroGraphAnzoGraph DBHeroicMicrosoft Azure Data ExplorerRaima Database Manager infoformerly named db_Vista
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Raima Database Manager (RDM) is an embedded time-series database optimized to run...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
Decreased time-to-market Industry-standard interfaces & tools for making your job...
» more
Typical application scenariosTypical use cases include: Internet of Things (IoT) Embedded In-Memory Database Time-Series...
» more
Key customersInfor, ABB, The Boeing Company, BAE Systems, Dow Jones, Dun & Bradstreet, Fujitsu,...
» more
Market metricsOver 30 000 applications developers worldwide have field-tested RDM products More...
» more
Licensing and pricing modelsJust as the technical aspects of Raima Database Manager are flexible, so are the...
» more
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