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DBMS > Microsoft Azure Data Explorer vs. Sequoiadb vs. Spark SQL

System Properties Comparison Microsoft Azure Data Explorer vs. Sequoiadb vs. Spark SQL

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonSequoiadb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformNewSQL database with distributed OLTP and SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMS infocolumn orientedDocument store
Relational DBMS
Relational 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteazure.microsoft.com/­services/­data-explorerwww.sequoiadb.comspark.apache.org/­sql
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerwww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMicrosoftSequoiadb Ltd.Apache Software Foundation
Initial release201920132014
Current releasecloud service with continuous releases3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoServer: AGPL; Client: Apache V2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Scala
Server operating systemshostedLinuxLinux
OS X
Windows
Data schemeFixed schema with schema-less datatypes (dynamic)schema-freeyes
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-typesyes infooid, date, timestamp, binary, regexyes
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.yesnono
Secondary indexesall fields are automatically indexedyesno
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
proprietary protocol using JSONJDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, RJavaScriptno
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoDocument is locked during a transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAzure Active Directory Authenticationsimple password-based access controlno

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More resources
Microsoft Azure Data ExplorerSequoiadbSpark SQL
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