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DBMS > Apache IoTDB vs. Graph Engine vs. Kdb vs. Microsoft Azure Data Explorer vs. TerminusDB

System Properties Comparison Apache IoTDB vs. Graph Engine vs. Kdb vs. Microsoft Azure Data Explorer vs. TerminusDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonKdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTerminusDB infoformer name was DataChemist  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineHigh performance Time Series DBMSFully managed big data interactive analytics platformScalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships
Primary database modelTime Series DBMSGraph DBMS
Key-value store
Time Series DBMS
Vector DBMS
Relational DBMS infocolumn orientedGraph DBMS
Secondary database modelsRelational DBMSDocument 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
Document store
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.17
Rank#325  Overall
#29  Graph DBMS
Websiteiotdb.apache.orgwww.graphengine.iokx.comazure.microsoft.com/­services/­data-explorerterminusdb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.graphengine.io/­docs/­manualcode.kx.comdocs.microsoft.com/­en-us/­azure/­data-explorerterminusdb.github.io/­terminusdb/­#
DeveloperApache Software FoundationMicrosoftKx Systems, a division of First Derivatives plcMicrosoftDataChemist Ltd.
Initial release201820102000 infokdb was released 2000, kdb+ in 200320192018
Current release1.1.0, April 20233.6, May 2018cloud service with continuous releases11.0.0, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoMIT Licensecommercial infofree 32-bit versioncommercialOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava.NET and CqProlog, Rust
Server operating systemsAll OS with a Java VM (>= 1.8).NETLinux
OS X
Solaris
Windows
hostedLinux
Data schemeyesyesyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyesyes 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.nonoyesyesno
Secondary indexesyesyes infotable attribute 'grouped'all fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenoSQL-like query language (q)Kusto Query Language (KQL), SQL subsetSQL-like query language (WOQL)
APIs and other access methodsJDBC
Native API
RESTful HTTP APIHTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
OWL
RESTful HTTP API
WOQL (Web Object Query Language)
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
F#
Visual Basic
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
JavaScript
Python
Server-side scripts infoStored proceduresyesyesuser defined functionsYes, possible languages: KQL, Python, Ryes
Triggersyesnoyes infowith viewsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioninghorizontal partitioningSharding infoImplicit feature of the cloud serviceGraph Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Journaling Streams
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkno infosimilar paradigm used for internal processingSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes infoin-memory journaling
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlyesrights management via user accountsAzure Active Directory AuthenticationRole-based access control
More information provided by the system vendor
Apache IoTDBGraph Engine infoformer name: TrinityKdbMicrosoft Azure Data ExplorerTerminusDB infoformer name was DataChemist
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
Apache IoTDBGraph Engine infoformer name: TrinityKdbMicrosoft Azure Data ExplorerTerminusDB infoformer name was DataChemist
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