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DBMS > AnzoGraph DB vs. Firebase Realtime Database vs. InterSystems IRIS vs. Microsoft Azure Data Explorer vs. TimesTen

System Properties Comparison AnzoGraph DB vs. Firebase Realtime Database vs. InterSystems IRIS vs. Microsoft Azure Data Explorer vs. TimesTen

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonInterSystems IRIS  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalabilityFully managed big data interactive analytics platformIn-Memory RDBMS compatible to Oracle
Primary database modelGraph DBMS
RDF store
Document storeDocument store
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMS infocolumn orientedRelational DBMS
Secondary database modelsDocument 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
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score13.64
Rank#39  Overall
#6  Document stores
Score3.54
Rank#84  Overall
#14  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#45  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.36
Rank#161  Overall
#75  Relational DBMS
Websitecambridgesemantics.com/­anzographfirebase.google.com/­products/­realtime-databasewww.intersystems.com/­products/­intersystems-irisazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmfirebase.google.com/­docs/­databasedocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.clsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­database/­timesten-18.1
DeveloperCambridge SemanticsGoogle infoacquired by Google 2014InterSystemsMicrosoftOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20182012201820191998
Current release2.3, January 20212023.3, June 2023cloud service with continuous releases11 Release 2 (11.2.2.8.0)
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Server operating systemsLinuxhostedAIX
Linux
macOS
Ubuntu
Windows
hostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeSchema-free and OWL/RDFS-schema supportschema-freedepending on used data modelFixed 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.nonoyesyesno
Secondary indexesnoyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.noyesKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
Android
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC++
Java
Python
Java
JavaScript
Objective-C
.Net
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresuser defined functions and aggregateslimited functionality with using 'rules'yesYes, possible languages: KQL, Python, RPL/SQL
TriggersnoCallbacks are triggered when data changesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityno infonot needed in graphsnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlAccess rights for users and rolesyes, based on authentication and database rulesyesAzure Active Directory Authenticationfine grained access rights according to SQL-standard
More information provided by the system vendor
AnzoGraph DBFirebase Realtime DatabaseInterSystems IRISMicrosoft Azure Data ExplorerTimesTen
Specific characteristicsInterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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More resources
AnzoGraph DBFirebase Realtime DatabaseInterSystems IRISMicrosoft Azure Data ExplorerTimesTen
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