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DBMS > Apache Drill vs. Apache IoTDB vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage

System Properties Comparison Apache Drill vs. Apache IoTDB vs. Microsoft Azure Data Explorer vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonApache IoTDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageAn 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 Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelDocument store
Relational DBMS
Time Series DBMSRelational DBMS infocolumn orientedWide column 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
Score1.95
Rank#127  Overall
#23  Document stores
#60  Relational DBMS
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Websitedrill.apache.orgiotdb.apache.orgazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdrill.apache.org/­docsiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software FoundationApache Software FoundationMicrosoftMicrosoft
Initial release2012201820192012
Current release1.20.3, January 20231.1.0, April 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemsLinux
OS X
Windows
All OS with a Java VM (>= 1.8)hostedhosted
Data schemeschema-freeyesFixed 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.nonoyesno
Secondary indexesnoyesall fields are automatically indexedno
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantSQL-like query languageKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
Native API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC++C
C#
C++
Go
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsyesYes, possible languages: KQL, Python, Rno
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud service
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.yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesIntegration with Hadoop and SparkSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourceyesnono
User concepts infoAccess controlDepending on the underlying data sourceyesAzure Active Directory AuthenticationAccess rights based on private key authentication or shared access signatures

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Apache DrillApache IoTDBMicrosoft Azure Data ExplorerMicrosoft Azure Table Storage
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