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DBMS > Amazon DynamoDB vs. Apache IoTDB vs. Atos Standard Common Repository vs. Microsoft Azure Data Explorer vs. Microsoft SQL Server

System Properties Comparison Amazon DynamoDB vs. Apache IoTDB vs. Atos Standard Common Repository vs. Microsoft Azure Data Explorer vs. Microsoft SQL Server

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksFully managed big data interactive analytics platformMicrosofts flagship relational DBMS
Primary database modelDocument store
Key-value store
Time Series DBMSDocument store
Key-value store
Relational DBMS infocolumn orientedRelational 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
Document store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score74.45
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score821.56
Rank#3  Overall
#3  Relational DBMS
Websiteaws.amazon.com/­dynamodbiotdb.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositoryazure.microsoft.com/­services/­data-explorerwww.microsoft.com/­en-us/­sql-server
Technical documentationdocs.aws.amazon.com/­dynamodbiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.microsoft.com/­en-us/­azure/­data-explorerlearn.microsoft.com/­en-US/­sql/­sql-server
DeveloperAmazonApache Software FoundationAtos Convergence CreatorsMicrosoftMicrosoft
Initial release20122018201620191989
Current release1.1.0, April 20231703cloud service with continuous releasesSQL Server 2022, November 2022
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoApache Version 2.0commercialcommercialcommercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
Implementation languageJavaJavaC++
Server operating systemshostedAll OS with a Java VM (>= 1.8)LinuxhostedLinux
Windows
Data schemeschema-freeyesSchema and schema-less with LDAP viewsFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesoptionalyes 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.noyesyesyes
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLnoSQL-like query languagenoKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsRESTful HTTP APIJDBC
Native API
LDAPMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C
C#
C++
Go
Java
Python
Scala
All languages with LDAP bindings.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
Server-side scripts infoStored proceduresnoyesnoYes, possible languages: KQL, Python, RTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Java
Triggersyes infoby integration with AWS Lambdayesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infocell divisionSharding infoImplicit feature of the cloud servicetables can be distributed across several files (horizontal partitioning); sharding through federation
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable 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.yes, but depending on the SQL-Server Edition
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Integration with Hadoop and SparkSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoACID across one or more tables within a single AWS account and regionnoAtomic execution of specific operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yesLDAP bind authenticationAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
Amazon DynamoDBApache IoTDBAtos Standard Common RepositoryMicrosoft Azure Data ExplorerMicrosoft SQL Server
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