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DBMS > AllegroGraph vs. EsgynDB vs. Google Cloud Datastore vs. InterSystems IRIS vs. Microsoft Azure Data Explorer

System Properties Comparison AllegroGraph vs. EsgynDB vs. Google Cloud Datastore vs. InterSystems IRIS vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInterSystems IRIS  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalabilityFully managed big data interactive analytics platform
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMSDocument storeDocument store
Key-value store
Object oriented DBMS
Relational DBMS
Relational 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
Score1.06
Rank#187  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score4.05
Rank#83  Overall
#14  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#45  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteallegrograph.comwww.esgyn.cncloud.google.com/­datastorewww.intersystems.com/­products/­intersystems-irisazure.microsoft.com/­services/­data-explorer
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlcloud.google.com/­datastore/­docsdocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.clsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperFranz Inc.EsgynGoogleInterSystemsMicrosoft
Initial release20042015200820182019
Current release8.0, December 20232023.3, June 2023cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnoyes
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
LinuxhostedAIX
Linux
macOS
Ubuntu
Windows
hosted
Data schemeyes infoRDF schemasyesschema-freedepending on used data modelFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes 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 possiblenonoyesyes
Secondary indexesyesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSPARQL is used as query languageyesSQL-like query language (GQL)yesKusto Query Language (KQL), SQL subset
APIs and other access methodsRESTful HTTP API
SPARQL
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON 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/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyes infoJavaScript or Common LispJava Stored Proceduresusing Google App EngineyesYes, possible languages: KQL, Python, R
TriggersyesnoCallbacks using the Google Apps Engineyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication between multi datacentersMulti-source replication using PaxosSource-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 methodsnoyesyes infousing Google Cloud DataflownoSpark 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 type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
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.nononoyesno
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesAzure Active Directory Authentication
More information provided by the system vendor
AllegroGraphEsgynDBGoogle Cloud DatastoreInterSystems IRISMicrosoft Azure Data Explorer
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
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