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DBMS > Informix vs. Microsoft Azure Data Explorer vs. Oracle NoSQL vs. RDF4J vs. SiriDB

System Properties Comparison Informix vs. Microsoft Azure Data Explorer vs. Oracle NoSQL vs. RDF4J vs. SiriDB

Editorial information provided by DB-Engines
NameInformix  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle NoSQL  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSiriDB  Xexclude from comparison
DescriptionA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataFully managed big data interactive analytics platformA multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodesRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Open Source Time Series DBMS
Primary database modelRelational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational DBMS infocolumn orientedDocument store
Key-value store
Relational DBMS
RDF storeTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
Document 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
Score17.12
Rank#34  Overall
#21  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score3.05
Rank#97  Overall
#17  Document stores
#16  Key-value stores
#50  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score0.07
Rank#378  Overall
#42  Time Series DBMS
Websitewww.ibm.com/­products/­informixazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­nosql/­technologies/­nosqlrdf4j.orgsiridb.com
Technical documentationinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
docs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­database/­other-databases/­nosql-database/­index.htmlrdf4j.org/­documentationdocs.siridb.com
DeveloperIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.MicrosoftOracleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Cesbit
Initial release19842019201120042017
Current release14.10.FC5, November 2020cloud service with continuous releases24.1, May 2024
License infoCommercial or Open Sourcecommercial infofree developer edition availablecommercialOpen Source infoProprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)Open Source infoEclipse Distribution License (EDL), v1.0.Open Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ and JavaJavaJavaC
Server operating systemsAIX
HP-UX
Linux
macOS
Solaris
Windows
hostedLinux
Solaris SPARC/x86
Linux
OS X
Unix
Windows
Linux
Data schemeyesFixed schema with schema-less datatypes (dynamic)Support Fixed schema and Schema-less deployment with the ability to interoperate between them.yes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyes infoSince Version 12.10 support for JSON/BSON datatypesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesoptionalyesyes infoNumeric data
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.yesnono
Secondary indexesyesall fields are automatically indexedyesyesyes
SQL infoSupport of SQLyesKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statementsnono
APIs and other access methodsJDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
HTTP API
Supported programming languages.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
Go
Java
JavaScript (Node.js)
Python
Java
PHP
Python
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresyesYes, possible languages: KQL, Python, Rnoyesno
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Electable source-replica replication per shard. Support distributed global deployment with Multi-region table featurenoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkwith Hadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency infodepending on configuration
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoconfigurable infoACID within a storage node (=shard)ACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infooff heap cacheyes
User concepts infoAccess controlUsers with fine-grained authentication, authorization, and auditing controlsAzure Active Directory AuthenticationAccess rights for users and rolesnosimple rights management via user accounts

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More resources
InformixMicrosoft Azure Data ExplorerOracle NoSQLRDF4J infoformerly known as SesameSiriDB
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