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DBMS > Amazon DynamoDB vs. Hive vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Data Explorer vs. Valentina Server

System Properties Comparison Amazon DynamoDB vs. Hive vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Data Explorer vs. Valentina Server

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons clouddata warehouse software for querying and managing large distributed datasets, built on HadoopGlobally distributed, horizontally scalable, multi-model database serviceFully managed big data interactive analytics platformObject-relational database and reports server
Primary database modelDocument store
Key-value store
Relational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMS infocolumn orientedRelational DBMS
Secondary database modelsSpatial DBMSDocument 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
Score74.45
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score27.71
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.21
Rank#325  Overall
#144  Relational DBMS
Websiteaws.amazon.com/­dynamodbhive.apache.orgazure.microsoft.com/­services/­cosmos-dbazure.microsoft.com/­services/­data-explorerwww.valentina-db.net
Technical documentationdocs.aws.amazon.com/­dynamodbcwiki.apache.org/­confluence/­display/­Hive/­Homelearn.microsoft.com/­azure/­cosmos-dbdocs.microsoft.com/­en-us/­azure/­data-explorervalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperAmazonApache Software Foundation infoinitially developed by FacebookMicrosoftMicrosoftParadigma Software
Initial release20122012201420191999
Current release3.1.3, April 2022cloud service with continuous releases5.7.5
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoApache Version 2commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedAll OS with a Java VMhostedhostedLinux
OS X
Windows
Data schemeschema-freeyesschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyes infoJSON typesyes 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.yes
Secondary indexesyesyesyes infoAll properties auto-indexed by defaultall fields are automatically indexedyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query languageKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Thrift
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ODBC
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C++
Java
PHP
Python
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceJavaScriptYes, possible languages: KQL, Python, Ryes
Triggersyes infoby integration with AWS LambdanoJavaScriptyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factoryes infoImplicit feature of the cloud serviceyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infoquery execution via MapReducewith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*Spark 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 ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Eventual 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 regionnoMulti-item ACID transactions with snapshot isolation within a partitionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and rolesAccess rights can be defined down to the item levelAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
Amazon DynamoDBHiveMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBMicrosoft Azure Data ExplorerValentina Server
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