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DBMS > MarkLogic vs. Spark SQL vs. UniData,UniVerse

System Properties Comparison MarkLogic vs. Spark SQL vs. UniData,UniVerse

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Editorial information provided by DB-Engines
NameMarkLogic  Xexclude from comparisonSpark SQL  Xexclude from comparisonUniData,UniVerse  Xexclude from comparison
DescriptionOperational and transactional Enterprise NoSQL databaseSpark SQL is a component on top of 'Spark Core' for structured data processingMultiValue database and application server with SQL mapping layer and meta database capabilities
Primary database modelDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSMultivalue DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score3.16
Rank#97  Overall
#2  Multivalue DBMS
Websitewww.marklogic.comspark.apache.org/­sqlwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidata
Technical documentationdocs.marklogic.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata
DeveloperMarkLogic Corp.Apache Software FoundationRocket Software
Initial release200120141985
Current release11.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial inforestricted free version is availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaC
Server operating systemsLinux
OS X
Windows
Linux
OS X
Windows
AIX
HP-UX
Linux
Solaris
Windows
Data schemeschema-free infoSchema can be enforcedyesschema-free
Typing infopredefined data types such as float or dateyesyesoptional
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.yesno
Secondary indexesyesnoyes
SQL infoSupport of SQLyes infoSQL92SQL-like DML and DDL statementsyes
APIs and other access methodsJava API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
JDBC
ODBC
Java API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
.Net
Basic infoU2 Basic
C
Java
Server-side scripts infoStored proceduresyes infovia XQuery or JavaScriptnoyes
Triggersyesnoyes infoU2 Basic
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infocan act as a resource manager in an XA/JTA transactionnoACID infoconfigurable
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.yes, with Range Indexesno
User concepts infoAccess controlRole-based access control at the document and subdocument levelsnoAccess rights according to SQL-standard and operating system based

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More resources
MarkLogicSpark SQLUniData,UniVerse
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