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DBMS > EXASOL vs. GeoMesa vs. Microsoft Azure Data Explorer vs. RDF4J vs. TDengine

System Properties Comparison EXASOL vs. GeoMesa vs. Microsoft Azure Data Explorer vs. RDF4J vs. TDengine

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonGeoMesa  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Fully managed big data interactive analytics platformRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Time Series DBMS and big data platform
Primary database modelRelational DBMSSpatial DBMSRelational DBMS infocolumn orientedRDF storeTime Series 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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websitewww.exasol.comwww.geomesa.orgazure.microsoft.com/­services/­data-explorerrdf4j.orggithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationwww.exasol.com/­resourceswww.geomesa.org/­documentation/­stable/­user/­index.htmldocs.microsoft.com/­en-us/­azure/­data-explorerrdf4j.org/­documentationdocs.tdengine.com
DeveloperExasolCCRi and othersMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.TDEngine, previously Taos Data
Initial release20002014201920042019
Current release4.0.5, February 2024cloud service with continuous releases3.0, August 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache License 2.0commercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaJavaC
Server operating systemshostedLinux
OS X
Unix
Windows
Linux
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yes infoRDF Schemasyes
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-typesyesyes
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.nonoyesno
Secondary indexesyesyesall fields are automatically indexedyesno
SQL infoSupport of SQLyesnoKusto Query Language (KQL), SQL subsetnoStandard SQL with extensions for time-series applications
APIs and other access methods.Net
JDBC
ODBC
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
RESTful HTTP API
Supported programming languagesJava
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
PHP
Python
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresuser defined functionsnoYes, possible languages: KQL, Python, Ryesno
Triggersyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesShardingdepending on storage layerSharding infoImplicit feature of the cloud servicenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layeryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistencydepending on storage layerEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID infoIsolation support depends on the API used
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.yesdepending on storage layerno
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardyes infodepending on the DBMS used for storageAzure Active Directory Authenticationnoyes
More information provided by the system vendor
EXASOLGeoMesaMicrosoft Azure Data ExplorerRDF4J infoformerly known as SesameTDengine
Specific characteristicsTDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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More resources
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