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DBMS > Microsoft Azure Data Explorer vs. Sadas Engine vs. SWC-DB vs. Teradata Aster

System Properties Comparison Microsoft Azure Data Explorer vs. Sadas Engine vs. SWC-DB vs. Teradata Aster

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonSadas Engine  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionFully managed big data interactive analytics platformSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsA high performance, scalable Wide Column DBMSPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMS infocolumn orientedRelational DBMSWide column storeRelational 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
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websiteazure.microsoft.com/­services/­data-explorerwww.sadasengine.comgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperMicrosoftSADAS s.r.l.Alex KashirinTeradata
Initial release2019200620202005
Current releasecloud service with continuous releases8.00.5, April 2021
License infoCommercial or Open Sourcecommercialcommercial infofree trial version availableOpen Source infoGPL V3commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++
Server operating systemshostedAIX
Linux
Windows
LinuxLinux
Data schemeFixed schema with schema-less datatypes (dynamic)yesschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
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-typesyesyes
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.yesnonoyes infoin Aster File Store
Secondary indexesall fields are automatically indexedyesyes
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetyesSQL-like query languageyes
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
Proprietary protocol
Thrift
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Groovy
Java
PHP
Python
C++C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, RnonoR packages
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynonono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
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'nono
User concepts infoAccess controlAzure Active Directory AuthenticationAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Microsoft Azure Data ExplorerSadas EngineSWC-DB infoSuper Wide Column DatabaseTeradata Aster
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