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DBMS > Apache IoTDB vs. MaxDB vs. Microsoft Azure Data Explorer vs. TimesTen vs. Titan

System Properties Comparison Apache IoTDB vs. MaxDB vs. Microsoft Azure Data Explorer vs. TimesTen vs. Titan

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonMaxDB infoformerly named Adabas-D  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTimesTen  Xexclude from comparisonTitan  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
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 robust and reliable RDBMS optimized to run all major SAP solutionsFully managed big data interactive analytics platformAn in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.Titan is a Graph DBMS optimized for distributed clusters.
Primary database modelTime Series DBMSRelational DBMSRelational DBMS infocolumn orientedRelational DBMSGraph 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#159  Overall
#14  Time Series DBMS
Score2.15
Rank#115  Overall
#55  Relational DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score1.26
Rank#164  Overall
#75  Relational DBMS
Websiteiotdb.apache.orgmaxdb.sap.comazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­timesten.htmlgithub.com/­thinkaurelius/­titan
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlmaxdb.sap.com/­documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­database/­other-databases/­timesten/­index.htmlgithub.com/­thinkaurelius/­titan/­wiki
DeveloperApache Software FoundationSAP, acquired from Software AG (Adabas-D) in 1997MicrosoftOracle infooriginally founded in HP Labs it was acquired by Oracle in 2005Aurelius, owned by DataStax
Initial release20181984201919982012
Current release1.1.0, April 20237.9.10.12, February 2024cloud service with continuous releasesRelease 22.1
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoLimited community edition freecommercialcommercialOpen Source infoApache license, version 2.0
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 languageJavaC++Java
Server operating systemsAll OS with a Java VM (>= 1.8)AIX
HP-UX
Linux
Solaris
Windows
hostedIBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
Linux
OS X
Unix
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yesyes
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 indexedyesyes
SQL infoSupport of SQLSQL-like query languageyesKusto Query Language (KQL), SQL subsetyesno
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
ODBC
WebDAV
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C#
Java
Perl
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Java
Node.js
PL/SQL
Python
Clojure
Java
Python
Server-side scripts infoStored proceduresyesyesYes, possible languages: KQL, Python, RPL/SQLyes
Triggersyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneSharding infoImplicit feature of the cloud servicenoneyes infovia pluggable storage backends
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.Multi-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyesyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby means of logfiles and checkpointsyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardAzure Active Directory Authenticationfine grained access rights according to SQL-standardUser authentification and security via Rexster Graph Server

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Apache IoTDBMaxDB infoformerly named Adabas-DMicrosoft Azure Data ExplorerTimesTenTitan
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