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DBMS > Apache Druid vs. Microsoft Azure AI Search vs. mSQL vs. OrigoDB vs. Spark SQL

System Properties Comparison Apache Druid vs. Microsoft Azure AI Search vs. mSQL vs. OrigoDB vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataSearch-as-a-service for web and mobile app developmentmSQL (Mini SQL) is a simple and lightweight RDBMSA fully ACID in-memory object graph databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMS
Time Series DBMS
Search engineRelational DBMSDocument store
Object oriented DBMS
Relational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score1.27
Rank#167  Overall
#77  Relational DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitedruid.apache.orgazure.microsoft.com/­en-us/­services/­searchhughestech.com.au/­products/­msqlorigodb.comspark.apache.org/­sql
Technical documentationdruid.apache.org/­docs/­latest/­designlearn.microsoft.com/­en-us/­azure/­searchorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsMicrosoftHughes TechnologiesRobert Friberg et alApache Software Foundation
Initial release2012201519942009 infounder the name LiveDB2014
Current release29.0.1, April 2024V14.4, October 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercial infofree licenses can be providedOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC#Scala
Server operating systemsLinux
OS X
Unix
hostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
Windows
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supportedyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesUser defined using .NET types and collectionsyes
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.nononono infocan be achieved using .NETno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL for queryingnoA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP APIJDBC
ODBC
.NET Client API
HTTP API
LINQ
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
Java
JavaScript
Python
C
C++
Delphi
Java
Perl
PHP
Tcl
.NetJava
Python
R
Scala
Server-side scripts infoStored proceduresnononoyesno
Triggersnononoyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infoImplicit feature of the cloud servicenonehorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infoImplicit feature of the cloud servicenoneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistencynone
Foreign keys infoReferential integritynononodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesnoyesyes
Durability infoSupport for making data persistentyesyesyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyes infousing Azure authenticationnoRole based authorizationno

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More resources
Apache DruidMicrosoft Azure AI SearchmSQL infoMini SQLOrigoDBSpark SQL
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