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DBMS > Apache IoTDB vs. Microsoft Azure Data Explorer vs. mSQL vs. Titan vs. TypeDB

System Properties Comparison Apache IoTDB vs. Microsoft Azure Data Explorer vs. mSQL vs. Titan vs. TypeDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonTitan  Xexclude from comparisonTypeDB infoformerly named Grakn  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 FlinkFully managed big data interactive analytics platformmSQL (Mini SQL) is a simple and lightweight RDBMSTitan is a Graph DBMS optimized for distributed clusters.TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language
Primary database modelTime Series DBMSRelational DBMS infocolumn orientedRelational DBMSGraph DBMSGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
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
Score1.19
Rank#176  Overall
#15  Time Series DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score1.67
Rank#151  Overall
#70  Relational DBMS
Score0.81
Rank#217  Overall
#19  Graph DBMS
#99  Relational DBMS
Websiteiotdb.apache.orgazure.microsoft.com/­services/­data-explorerhughestech.com.au/­products/­msqlgithub.com/­thinkaurelius/­titantypedb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.microsoft.com/­en-us/­azure/­data-explorergithub.com/­thinkaurelius/­titan/­wikitypedb.com/­docs
DeveloperApache Software FoundationMicrosoftHughes TechnologiesAurelius, owned by DataStaxVaticle
Initial release20182019199420122016
Current release1.1.0, April 2023cloud service with continuous releases4.4, October 20212.26.3, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infofree licenses can be providedOpen Source infoApache license, version 2.0Open Source infoGPL Version 3, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCJavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)hostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)yesyesyes
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyesyes
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.noyesnono
Secondary indexesyesall fields are automatically indexedyesyesyes
SQL infoSupport of SQLSQL-like query languageKusto Query Language (KQL), SQL subsetA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersnono
APIs and other access methodsJDBC
Native API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Delphi
Java
Perl
PHP
Tcl
Clojure
Java
Python
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresyesYes, possible languages: KQL, Python, Rnoyesno
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoImplicit feature of the cloud servicenoneyes infovia pluggable storage backendsSharding infoby using Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneyesMulti-source replication infoby using Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyes infovia Faunus, a graph analytics engineyes infoby using Apache Kafka and Apache Zookeeper
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
noneEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes infoRelationships in graphno infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesnoyesyes
Durability infoSupport for making data persistentyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlyesAzure Active Directory AuthenticationnoUser authentification and security via Rexster Graph Serveryes infoat REST API level; other APIs in progress
More information provided by the system vendor
Apache IoTDBMicrosoft Azure Data ExplorermSQL infoMini SQLTitanTypeDB infoformerly named Grakn
Specific characteristicsTypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Licensing and pricing modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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Apache IoTDBMicrosoft Azure Data ExplorermSQL infoMini SQLTitanTypeDB infoformerly named Grakn
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