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DBMS > IRONdb vs. Microsoft Azure Data Explorer vs. OrigoDB vs. RDF4J vs. Teradata Aster

System Properties Comparison IRONdb vs. Microsoft Azure Data Explorer vs. OrigoDB vs. RDF4J vs. Teradata Aster

Editorial information provided by DB-Engines
NameIRONdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOrigoDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTeradata Aster  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed 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 fully ACID in-memory object graph databaseRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Platform for big data analytics on multistructured data sources and types
Primary database modelTime Series DBMSRelational DBMS infocolumn orientedDocument store
Object oriented DBMS
RDF storeRelational 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
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitewww.circonus.com/solutions/time-series-database/azure.microsoft.com/­services/­data-explorerorigodb.comrdf4j.org
Technical documentationdocs.circonus.com/irondb/category/getting-starteddocs.microsoft.com/­en-us/­azure/­data-explorerorigodb.com/­docsrdf4j.org/­documentation
DeveloperCirconus LLC.MicrosoftRobert Friberg et alSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Teradata
Initial release201720192009 infounder the name LiveDB20042005
Current releaseV0.10.20, January 2018cloud service with continuous releases
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen Source infoEclipse Distribution License (EDL), v1.0.commercial
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 and C++C#Java
Server operating systemsLinuxhostedLinux
Windows
Linux
OS X
Unix
Windows
Linux
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yesyes infoRDF SchemasFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
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-typesUser defined using .NET types and collectionsyesyes
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.noyesno infocan be achieved using .NETyes infoin Aster File Store
Secondary indexesnoall fields are automatically indexedyesyesyes
SQL infoSupport of SQLSQL-like query language (Circonus Analytics Query Language: CAQL)Kusto Query Language (KQL), SQL subsetnonoyes
APIs and other access methodsHTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
HTTP API
LINQ
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
ADO.NET
JDBC
ODBC
OLE DB
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
.NetJava
PHP
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes, in LuaYes, possible languages: KQL, Python, RyesyesR packages
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoDomain Eventsyesno
Partitioning methods infoMethods for storing different data on different nodesAutomatic, metric affinity per nodeSharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronizednoneSharding
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.Source-replica replicationnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency per node, eventual consistency across nodesEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoWrite ahead logyes 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.nonoyesno
User concepts infoAccess controlnoAzure Active Directory AuthenticationRole based authorizationnofine grained access rights according to SQL-standard

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More resources
IRONdbMicrosoft Azure Data ExplorerOrigoDBRDF4J infoformerly known as SesameTeradata Aster
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