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DBMS > AllegroGraph vs. AnzoGraph DB vs. GridGain vs. Heroic vs. Microsoft Azure Data Explorer

System Properties Comparison AllegroGraph vs. AnzoGraph DB vs. GridGain vs. Heroic vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonAnzoGraph DB  Xexclude from comparisonGridGain  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Data Explorer  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 virtualizationGridGain is an in-memory computing platform, built on Apache IgniteTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully managed big data interactive analytics platform
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Graph DBMS
RDF store
Key-value store
Relational DBMS
Time Series DBMSRelational DBMS infocolumn oriented
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
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websiteallegrograph.comcambridgesemantics.com/­anzographwww.gridgain.comgithub.com/­spotify/­heroicazure.microsoft.com/­services/­data-explorer
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmwww.gridgain.com/­docs/­index.htmlspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperFranz Inc.Cambridge SemanticsGridGain Systems, Inc.SpotifyMicrosoft
Initial release20042018200720142019
Current release8.0, December 20232.3, January 2021GridGain 8.5.1cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercial infofree trial version availablecommercialOpen Source infoApache 2.0commercial
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 languageJava, C++, .NetJava
Server operating systemsLinux
OS X
Windows
LinuxLinux
OS X
Solaris
Windows
hosted
Data schemeyes infoRDF schemasSchema-free and OWL/RDFS-schema supportyesschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyes 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 indexesyesnoyesyes infovia Elasticsearchall fields are automatically indexed
SQL infoSupport of SQLSPARQL is used as query languageSPARQL and SPARQL* as primary query language. Cypher preview.ANSI-99 for query and DML statements, subset of DDLnoKusto Query Language (KQL), SQL subset
APIs and other access methodsRESTful HTTP API
SPARQL
Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
C++
Java
Python
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispuser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)noYes, possible languages: KQL, Python, R
Triggersyesnoyes (cache interceptors and events)noyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeswith FederationAutomatic shardingShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication in MPP-Clusteryes (replicated cache)yesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoKerberos/HDFS data loadingyes (compute grid and hadoop accelerator)noSpark 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 Consistency in MPP-ClusterImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynono infonot needed in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnono
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.noyesyesnono
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess rights for users and rolesSecurity Hooks for custom implementationsAzure Active Directory Authentication
More information provided by the system vendor
AllegroGraphAnzoGraph DBGridGainHeroicMicrosoft 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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