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DBMS > Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database vs. Sadas Engine vs. Vertica vs. YTsaurus

System Properties Comparison Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database vs. Sadas Engine vs. Vertica vs. YTsaurus

Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonSadas Engine  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonYTsaurus  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformDatabase as a Service offering with high compatibility to Microsoft SQL ServerSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.YTsaurus is an open source platform for distributed storage and processing.
Primary database modelRelational DBMS infocolumn orientedRelational DBMSRelational DBMSRelational DBMS infoColumn orientedDocument store
Key-value 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
Document store
Graph DBMS
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Score0.11
Rank#340  Overall
#45  Document stores
#50  Key-value stores
Websiteazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­products/­azure-sql/­databasewww.sadasengine.comwww.vertica.comytsaurus.tech
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.microsoft.com/­en-us/­azure/­azure-sqlwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationvertica.com/­documentationytsaurus.tech/­docs/­en
DeveloperMicrosoftMicrosoftSADAS s.r.l.OpenText infopreviously Micro Focus and Hewlett PackardYandex
Initial release20192010200620052023
Current releasecloud service with continuous releasesV128.012.0.3, January 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree trial version availablecommercial infoLimited community edition freeOpen Source infoApache License, Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C++C++
Server operating systemshostedhostedAIX
Linux
Windows
LinuxUbuntu
Data schemeFixed schema with schema-less datatypes (dynamic)yesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyesyesyes
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.yesyesnonono
Secondary indexesall fields are automatically indexedyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetyesyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.YQL, an SQL-based language, is supported
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
C++
Go
Java
JavaScript
Python
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, RTransact SQLnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioninghorizontal partitioning, hierarchical partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, with always 3 replicas availablenoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono infoBi-directional Spark integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
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.noyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlAzure Active Directory Authenticationfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashAccess Control Lists
More information provided by the system vendor
Microsoft Azure Data ExplorerMicrosoft Azure SQL Database infoformerly SQL AzureSadas EngineVertica infoOpenText™ Vertica™YTsaurus
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
Microsoft Azure Data ExplorerMicrosoft Azure SQL Database infoformerly SQL AzureSadas EngineVertica infoOpenText™ Vertica™YTsaurus
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