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DBMS > Infobright vs. Microsoft Azure Data Explorer vs. SiteWhere vs. Spark SQL

System Properties Comparison Infobright vs. Microsoft Azure Data Explorer vs. SiteWhere vs. Spark SQL

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Editorial information provided by DB-Engines
NameInfobright  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSiteWhere  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionHigh performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendFully managed big data interactive analytics platformM2M integration platform for persisting/querying time series dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMS infocolumn orientedTime Series DBMSRelational 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
Score0.96
Rank#194  Overall
#91  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.06
Rank#356  Overall
#35  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteignitetech.com/­softwarelibrary/­infobrightdbazure.microsoft.com/­services/­data-explorergithub.com/­sitewhere/­sitewherespark.apache.org/­sql
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorersitewhere1.sitewhere.io/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperIgnite Technologies Inc.; formerly InfoBright Inc.MicrosoftSiteWhereApache Software Foundation
Initial release2005201920102014
Current releasecloud service with continuous releases3.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016commercialOpen Source infoCommon Public Attribution License Version 1.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaScala
Server operating systemsLinux
Windows
hostedLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)predefined schemeyes
Typing infopredefined data types such as float or dateyesyes 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.noyesnono
Secondary indexesno infoKnowledge Grid Technology used insteadall fields are automatically indexednono
SQL infoSupport of SQLyesKusto Query Language (KQL), SQL subsetnoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP RESTJDBC
ODBC
Supported programming languages.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Rno
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceSharding infobased on HBaseyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infobased on HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
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.yesnonono
User concepts infoAccess controlfine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesAzure Active Directory AuthenticationUsers with fine-grained authorization conceptno

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More resources
InfobrightMicrosoft Azure Data ExplorerSiteWhereSpark SQL
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