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DBMS > EXASOL vs. IRONdb vs. Microsoft Azure Data Explorer vs. RDFox

System Properties Comparison EXASOL vs. IRONdb vs. Microsoft Azure Data Explorer vs. RDFox

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Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRDFox  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully managed big data interactive analytics platformHigh performance knowledge graph and semantic reasoning engine
Primary database modelRelational DBMSTime Series DBMSRelational DBMS infocolumn orientedGraph DBMS
RDF store
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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Websitewww.exasol.comwww.circonus.com/solutions/time-series-database/azure.microsoft.com/­services/­data-explorerwww.oxfordsemantic.tech
Technical documentationwww.exasol.com/­resourcesdocs.circonus.com/irondb/category/getting-starteddocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oxfordsemantic.tech
DeveloperExasolCirconus LLC.MicrosoftOxford Semantic Technologies
Initial release2000201720192017
Current releaseV0.10.20, January 2018cloud service with continuous releases6.0, Septermber 2022
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C++
Server operating systemsLinuxhostedLinux
macOS
Windows
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yes infoRDF schemas
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyes 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.nonoyes
Secondary indexesyesnoall fields are automatically indexed
SQL infoSupport of SQLyesSQL-like query language (Circonus Analytics Query Language: CAQL)Kusto Query Language (KQL), SQL subsetno
APIs and other access methods.Net
JDBC
ODBC
WebSocket
HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
SPARQL 1.1
Supported programming languagesJava
Lua
Python
R
.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
C
Java
Server-side scripts infoStored proceduresuser defined functionsyes, in LuaYes, possible languages: KQL, Python, R
Triggersyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeSharding infoImplicit feature of the cloud service
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.replication via a shared file system
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesEventual Consistency
Immediate Consistency
Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardnoAzure Active Directory AuthenticationRoles, resources, and access types

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More resources
EXASOLIRONdbMicrosoft Azure Data ExplorerRDFox
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