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DBMS > IRONdb vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage vs. RDF4J vs. TypeDB

System Properties Comparison IRONdb vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage vs. RDF4J vs. TypeDB

Editorial information provided by DB-Engines
NameIRONdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTypeDB infoformerly named Grakn  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully managed big data interactive analytics platformA Wide Column Store for rapid development using massive semi-structured datasetsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language
Primary database modelTime Series DBMSRelational DBMS infocolumn orientedWide column storeRDF storeGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
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
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score4.92
Rank#73  Overall
#6  Wide column stores
Score0.71
Rank#231  Overall
#9  RDF stores
Score0.81
Rank#217  Overall
#19  Graph DBMS
#99  Relational DBMS
Websitewww.circonus.com/solutions/time-series-database/azure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­services/­storage/­tablesrdf4j.orgtypedb.com
Technical documentationdocs.circonus.com/irondb/category/getting-starteddocs.microsoft.com/­en-us/­azure/­data-explorerrdf4j.org/­documentationtypedb.com/­docs
DeveloperCirconus LLC.MicrosoftMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Vaticle
Initial release20172019201220042016
Current releaseV0.10.20, January 2018cloud service with continuous releases2.26.3, January 2024
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoGPL Version 3, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++JavaJava
Server operating systemsLinuxhostedhostedLinux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)schema-freeyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyes infotext, numeric, histogramsyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyesyes
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.noyesnono
Secondary indexesnoall fields are automatically indexednoyesyes
SQL infoSupport of SQLSQL-like query language (Circonus Analytics Query Language: CAQL)Kusto Query Language (KQL), SQL subsetnonono
APIs and other access methodsHTTP APIMicrosoft 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
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresyes, in LuaYes, possible languages: KQL, Python, Rnoyesno
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyesno
Partitioning methods infoMethods for storing different data on different nodesAutomatic, metric affinity per nodeSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud servicenoneSharding infoby using Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter awareyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneMulti-source replication infoby using Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonoyes infoby using Apache Kafka and Apache Zookeeper
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency per node, eventual consistency across nodesEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic lockingACID infoIsolation support depends on the API usedACID
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.nononono
User concepts infoAccess controlnoAzure Active Directory AuthenticationAccess rights based on private key authentication or shared access signaturesnoyes infoat REST API level; other APIs in progress
More information provided by the system vendor
IRONdbMicrosoft Azure Data ExplorerMicrosoft Azure Table StorageRDF4J infoformerly known as SesameTypeDB infoformerly named Grakn
Specific characteristicsTypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Licensing and pricing modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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More resources
IRONdbMicrosoft Azure Data ExplorerMicrosoft Azure Table StorageRDF4J infoformerly known as SesameTypeDB infoformerly named Grakn
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