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DBMS > 4D vs. Apache IoTDB vs. Microsoft Azure Data Explorer vs. XTDB

System Properties Comparison 4D vs. Apache IoTDB vs. Microsoft Azure Data Explorer vs. XTDB

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonApache IoTDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemAn 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 platformA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSTime Series DBMSRelational DBMS infocolumn orientedDocument store
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
Score2.47
Rank#110  Overall
#54  Relational DBMS
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.18
Rank#332  Overall
#46  Document stores
Websitewww.4d.comiotdb.apache.orgazure.microsoft.com/­services/­data-explorergithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationdeveloper.4d.comiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.microsoft.com/­en-us/­azure/­data-explorerwww.xtdb.com/­docs
Developer4D, IncApache Software FoundationMicrosoftJuxt Ltd.
Initial release1984201820192019
Current releasev20, April 20231.1.0, April 2023cloud service with continuous releases1.19, September 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaClojure
Server operating systemsOS X
Windows
All OS with a Java VM (>= 1.8)hostedAll OS with a Java 8 (and higher) VM
Linux
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, extensible-data-notation format
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.yesnoyesno
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLyes infoclose to SQL 92SQL-like query languageKusto Query Language (KQL), SQL subsetlimited SQL, making use of Apache Calcite
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
JDBC
Native API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP REST
JDBC
Supported programming languages4D proprietary IDE
PHP
C
C#
C++
Go
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Clojure
Java
Server-side scripts infoStored proceduresyesyesYes, possible languages: KQL, Python, Rno
Triggersyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationselectable 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.yes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and SparkSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlUsers and groupsyesAzure Active Directory Authentication

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More resources
4D infoformer name: 4th DimensionApache IoTDBMicrosoft Azure Data ExplorerXTDB infoformerly named Crux
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