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DBMS > Apache IoTDB vs. IBM Db2 warehouse vs. Microsoft Azure Data Explorer vs. Warp 10

System Properties Comparison Apache IoTDB vs. IBM Db2 warehouse vs. Microsoft Azure Data Explorer vs. Warp 10

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonWarp 10  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 FlinkCloud-based data warehousing serviceFully managed big data interactive analytics platformTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelTime Series DBMSRelational DBMSRelational DBMS infocolumn orientedTime 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.37
Rank#160  Overall
#74  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websiteiotdb.apache.orgwww.ibm.com/­products/­db2/­warehouseazure.microsoft.com/­services/­data-explorerwww.warp10.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.microsoft.com/­en-us/­azure/­data-explorerwww.warp10.io/­content/­02_Getting_started
DeveloperApache Software FoundationIBMMicrosoftSenX
Initial release2018201420192015
Current release1.1.0, April 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)hostedhostedLinux
OS X
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)schema-free
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-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.nono infoImport/export of XML data possibleyesno
Secondary indexesyesyesall fields are automatically indexedno
SQL infoSupport of SQLSQL-like query languageyesKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBC
Native API
.NET Client API
JDBC
ODBC
OLE DB
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Jupyter
WebSocket
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesPL/SQL, SQL PLYes, possible languages: KQL, Python, Ryes infoWarpScript
Triggersyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infoImplicit feature of the cloud serviceSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknoSpark 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
Immediate Consistency infobased on HBase
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesyesnoyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardAzure Active Directory AuthenticationMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Apache IoTDBIBM Db2 warehouse infoformerly named IBM dashDBMicrosoft Azure Data ExplorerWarp 10
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